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Open Access Article
1 - Short-term prediction of carbon monoxide gas concentration in the air of Ahvaz city using artificial neural network analysis
Maryam Kavosi سیما سبزعلی پور hossein fathianIntroduction: Air pollution in cities is one of the most critical environmental problems, representing a constant and severe threat to both the health and hygiene of society and the environment. The primary air pollutants include nitrogen oxides, with a particular empha MoreIntroduction: Air pollution in cities is one of the most critical environmental problems, representing a constant and severe threat to both the health and hygiene of society and the environment. The primary air pollutants include nitrogen oxides, with a particular emphasis on nitrogen dioxide, sulfur oxides, especially sulfur dioxide, hydrocarbons, carbon monoxide (CO), carbon dioxide, and suspended particles. Ahvaz, a metropolis in Iran, stands out as one of the most polluted cities. Effective environmental management, particularly in addressing air pollution, is of paramount importance. This research aims to predict the concentration of CO pollutants in Ahvaz city for the first seven days of 2015. Materials and Methods: Based on previous studies, meteorological variables including weather, air temperature and wind speed were selected as gas input titles in the network for gas prediction. CO gas was procured in 2014 through the Environmental Protection Organization of Ahvaz city. In order to develop the Multilayer Perceptron (MLP) neural network, Neuro Solution5 software was used to create the neural network, 70% of the data was used for training (validation), 15% for testing, and the remaining 15% for validating the results of the network. is used. was used. Results and Discussion: In order to determine the best MLP network structure for short-term prediction of CO gas concentration, different structures were considered in terms of the number of intermediate layers, the type of network training algorithm, the type of transfer function, the number of intermediate layer neurons and the number of repetitions (Epoch) of training. The results showed that the MLP network with a structure of 1-5-3 (that is, 3 input neurons, 5 neurons in the middle layer and one neuron for the output layer) with 1500 repetitions of training per Tansig transfer function (Tansant Sigmoid) and Traingdm training algorithm (reduction gradient with momentum), is the best MLP network. In addition, the values of NSE, RMSE and MAE statistical indices for the network training stage are equal to 0.72, 0.22 and 0.15 respectively. Conclusion: Air pollution, the primary environmental challenge in Ahvaz, arises from the intersection of traffic and the oil industry. Its impacts on health and the environment necessitate comprehensive investigation. In this study, an MLP network was employed to predict CO gas concentration values in the air of Ahvaz city. The findings demonstrate that the network's accuracy and performance in forecasting CO gas concentration are at an optimal level. As this research progresses, it is recommended to extend the prediction to other gaseous pollutants and to employ optimization algorithms for determining the optimal structure of the artificial neural network Manuscript profile -
Open Access Article
2 - Investigating the effect of the quality of internal audit performance on the accuracy of profit forecasting by managers of companies listed on the Tehran Stock Exchange
Massoumeh Latifi Benmaran Shahrzad SerajPurpose: The purpose of this research is to investigate the effect of the quality of internal audit performance on the accuracy of managers' profit forecast. Methodology: The data of 136 companies listed on the Iran Stock Exchange were used during the years 2017 to 202 MorePurpose: The purpose of this research is to investigate the effect of the quality of internal audit performance on the accuracy of managers' profit forecast. Methodology: The data of 136 companies listed on the Iran Stock Exchange were used during the years 2017 to 2021. Hypotheses were tested by multiple regression method considering the fixed effects of year and industry. Findings: The results of the statistical tests showed that there is a significant relationship between the quality of the internal audit and the accuracy of the company's profit forecast. Originality: Management forecasts are disclosures made by companies to communicate information about their future performance to shareholders. These disclosures are voluntary and are intended to reduce information asymmetry between management and shareholders. Inaccurate forecasts can be very costly for managers and question the credibility of managers and show managerial incompetence. The quality of the internal audit function reduces the likelihood of erroneous, biased, or incomplete information in management reports that managers use to improve their profit forecasts. Manuscript profile -
Open Access Article
3 - Investigating the possibility of biasing recommendation algorithms from users' rating behavior in online social networks
Mehdi Safarpour Seyed Hadi Yaghobian Karamollah BagheriFard razieh malekhoseini Samad NejatianAs online social networks become more widely used, there is a growing focus on the role of recommender algorithms within these platforms. It is important to assess the accuracy of these algorithms in providing suitable recommendations. Our research demonstrates that the MoreAs online social networks become more widely used, there is a growing focus on the role of recommender algorithms within these platforms. It is important to assess the accuracy of these algorithms in providing suitable recommendations. Our research demonstrates that the presence of individuals and acquaintances within social networks influences user behavior in ways that are largely psychological. Many user actions on a post are influenced by their respect or closeness to the post's owner. This article explores how the predictability of user behavior towards posts from friends and acquaintances highlights the impact of emotional connections stemming from stable social relationships on post acceptance. It also raises concerns about the potential for incorrect recommendations in algorithms based on collaborative filtering due to data bias caused by these factors. Manuscript profile -
Open Access Article
4 - Improving Web Recommendation Systems via Feature Engineering for Anticipating User's Subsequent Links
Vahid Saffari Karamolah BagheriFard Hamid Parvin Samad Nejatian Vahide RezaieGiven the remarkable growth in online content and extensive user engagement, understanding user behavior and providing accurate content recommendations stands as a significant challenge in data mining and recommendation systems. This article introduces a comprehensive a MoreGiven the remarkable growth in online content and extensive user engagement, understanding user behavior and providing accurate content recommendations stands as a significant challenge in data mining and recommendation systems. This article introduces a comprehensive approach to enhance user profiling accuracy and increase precision in web page recommendations. It initiates this process by introducing an innovative feature called "user engagement duration with web pages," significantly aiding in improving user profiles. Leveraging these enriched profiles facilitates predicting a user's next web page visit. Evaluating this model, comparison with a scenario lacking this new feature demonstrates a substantial increase in prediction accuracy upon its inclusion. Additionally, we delve into cluster analysis, employing k-means and k-medoids algorithms, where k-medoids demonstrate greater diversity in sample clustering. The paper establishes the superiority of using k-medoids in this domain and emphasizes the importance of determining optimal cluster sizes. Ultimately, this research culminates in developing a web recommendation system capable of highly accurate predictions regarding the user's next web destination. Hence, the proposed approach enhances the model's precision in recommending links to users and promises further advancements in this field. Manuscript profile -
Open Access Article
5 - Presenting A model to predict the Educational and Research Activities Outsourcing Model in Organizations Governmental
Amir Navidi Ali Taghipour Zahir Seyed Ali Akbar AhmadiThe anticipated activities as a good way to deal with complexity and uncertainty in decision-making and ensure success in the field of outsourcing is considered. The aim of this study was to Presenting the Educational and Research Activities Outsourcing Model in Organiz MoreThe anticipated activities as a good way to deal with complexity and uncertainty in decision-making and ensure success in the field of outsourcing is considered. The aim of this study was to Presenting the Educational and Research Activities Outsourcing Model in Organizations Governmental in Tehran/Iran. To this end, all employees and managers include 468 staffs were participated in present study, among them 211 were selected by Cochran formula and based on ratio multilevel cluster sampling. Data were collected by self questionnaires that the questions of getting a standard questionnaire. Data analysis was done using structural equation modeling by software Smart PLS 2 in two parts, the measurement model and structural section. In the first part, technical characteristics of the questionnaires including reliability, validity, convergent and divergent validity were evaluated. In the second part, software significant coefficients were used to evaluate the hypothesis. The findings of the study indicated that factors such as organizational, managerial, technical and structural factors and actors associated with the contractor in the process of outsourcing success training activities and research organizations are involved and influential. Manuscript profile -
Open Access Article
6 - Studying the concepts and basics of back-casting and comparing it with forecasting and visioning
معصومه کاظمی حسن gH نفیسه کاظمی اعظم BAOne of the most important goals of future study is to develop knowledge and to conceive a complicated set of possible futures and, as a result, paving the ground to create and to expand the best guidelines to face with confronting challenges. As a result, active and pro MoreOne of the most important goals of future study is to develop knowledge and to conceive a complicated set of possible futures and, as a result, paving the ground to create and to expand the best guidelines to face with confronting challenges. As a result, active and provocative decision making is ideal under such circumstances. Due to its normative nature and its emphasis on desired futures and considering uncertain conditions, back-casting is one of the best approaches to confront such challenges. Present study is conducted to investigate this approach on growing future study field. In this research, back-casting emergence trend, types of back-casting, steps of back-casting and its functionality are explained and this approach is contemplated. Also, forecasting and visioning methods are briefly reviewed and, ultimately, back-casting is compared with forecasting format as a contrary approach by considering a philosophical view against lack of justification, uncertainty against determinism and teleology against causality. It is also compared with visioning to open a window to conceive differences between back-casting and other techniques as guidance in using such techniques in practice Manuscript profile -
Open Access Article
7 - Presenting a new model for ATM demand scenario
Alireza Agha Gholizadeh Sayyar Mohamadreza Motadel Alireza Pour ebrahimiIn today's competitive world, the ability to recognize predict customer demand is an important issue for the success of organizations. And since ATMs are one of the most important channels for cash distribution and one of the most fundamental criteria for assessing the MoreIn today's competitive world, the ability to recognize predict customer demand is an important issue for the success of organizations. And since ATMs are one of the most important channels for cash distribution and one of the most fundamental criteria for assessing the level of service to banks,In this paper, the number of referrers to ATM devices is reviewed based on the timing and location of the devices. This article seeks to find a dynamic and functional model for predicting the number of referrers to each ATM depending on the time and location of the device. Hence, 378 ATM machines were used throughout the city of Tehran for a time period of one month, containing 69,418 records. Finally, with the help of clustering of statistical data in spatial and temporal dimensions, this model finally succeeds in learning the pattern in the macro data, and based on the decision tree, the predictor can predict the number of referents to each device, which after the algorithm is presented. In order to improve the quality of banking services and improve the performance of the ATM network, it is proposed to combine the optimal location of ATMs in spatial and temporal dimensions. Manuscript profile -
Open Access Article
8 - The prediction of Bankruptcy Risk Investigation Using Artificial Neural Networks Based on Multilayer Perceptron Approach (Empirical Evidence: Tehran Stock Exchange)
Somayeh Saroei Hamid Reza Vkili Fard Ghodratolah Taleb NiaThe aim of this research is Identification of the effective factors on bankruptcy prediction of Iranian companies by findings of artificial neural network (ANN) system based on Multilayer Perceptron Approach (PS) , and providing an appropriate statistical model for esti MoreThe aim of this research is Identification of the effective factors on bankruptcy prediction of Iranian companies by findings of artificial neural network (ANN) system based on Multilayer Perceptron Approach (PS) , and providing an appropriate statistical model for estimating the bankruptcy of Iranian companies by using the findings of The ANN implementation. we seek to answer the following question: Are we able to design a valid statistical model by using findings of artificial neural network (ANN) system to predict the bankruptcy of Iranian companies? The statistical population in this study is all of listed companies in Tehran Stock Exchange. By considering the criteria and method of systematic deletion, 172 companies from this statistical society have been selected as the sample in this research from 2007 to 2016. In order to make statistical analyzes in this study, we used from methods such as artificial neural network system based on multilevel perceptron approach, binary logistic regression, and tests such as Akaic, Schwarz, Hanan Quinn and Z wang test. The results of the analysis of the research data show that the ANN system can identify of the factors affecting on bankruptcy of Iranian companies in the year before bankruptcy by Precision equal 98%. Manuscript profile -
Open Access Article
9 - Technology Forecasting Based on Text Mining Patents and Cluster Analysis: Case Study Photovoltaic Technology
Zohre Bayanloo Habib Zare AhmadabadiNowadays, solar energy has been utilized in various ways and photovoltaic technology is one of them. Photovoltaic phenomena is a phenomena in which solar energy converts to the electrical energy “direct”. Shrinkage of fossil fuel resources as the curre MoreNowadays, solar energy has been utilized in various ways and photovoltaic technology is one of them. Photovoltaic phenomena is a phenomena in which solar energy converts to the electrical energy “direct”. Shrinkage of fossil fuel resources as the current main source of energy, is one of the main concerns of today’s world. Because of the solar energy has attracted attentions as an alternative for fossil fuels recently. Technology forecasting has been defined as pre-realization of promising future technology progresses and assessment of its potential. Researchers use numerous methods to forecast technology and analysis of patent is one of them. In this article international patents, related to the area, which are registered in USPTO from 1985 to 2016 has been extracted. By implementation of text mining and two step clustering approach, it turns out that there is research gaps in this sector of technology which is not considered. As the result, research gaps and future research opportunities for researchers were identified and presented. Manuscript profile -
Open Access Article
10 - An Analysis of the Energy Consumption Status in the Framework of Future Study Case Study: Tabriz City
Abolfazl Ghanbari Musa Vaezi Zahra AmjadiBackground: The increasing importance of energy resources in the formation and growth of economic processes, as well as the need to exploit these resources, based on environmental considerations and sustainable economic and social development, highlights the issue of id MoreBackground: The increasing importance of energy resources in the formation and growth of economic processes, as well as the need to exploit these resources, based on environmental considerations and sustainable economic and social development, highlights the issue of identifying and Future Study of the factors affecting energy consumption. Objective: The present research studies the status of energy consumption in Tabriz city in the framework of Foresight. Methods: This research is applied and descriptive-analytic. The Delphi method and the group of experts have been used to identify the factors affecting energy consumption. After analyzing the factors, 40 factors were identified and selected as influential factors. Using MICMAC software, the interactive effects analysis method has been identified. Finally, out of 40 factors, 16 main factors were selected as effective key proponents. Findings: Based on the data included in the questionnaire and the Wizard scenario software analysis, there are five strong scenarios, of which two scenarios are desirable conditions, a scenario of critical conditions, and two other scenarios of intermediate conditions. 13 scenarios with high adaptability and 292 poor scenarios. Initial studies of 13 scenarios show that the relative relativity of undesirable numbers is favorable on desired conditions. Apart from a few limited scenarios that have the characteristics that are desirable and progressing, the rest of the scenarios do not have a good future. Conclusion: The main result of this research is that the future energy consumption situation in Tabriz will continue to be a continuation of the current situation with an unfavorable and unfavorable situation. Manuscript profile -
Open Access Article
11 - Cluster Analysis of Iran's Position in the World and Future Trends Based on Good Governance Components
Mona Ahani Morteza Mosakhani Reza Najafbeigi Mohammad Ali AfsharkazemiThe Study of good governance and the quality of government institutions is a debate that began in the 90's. Good governance, which consists of six components: control of corruption, government effectiveness, political stability and absence of violence, regulatory qualit MoreThe Study of good governance and the quality of government institutions is a debate that began in the 90's. Good governance, which consists of six components: control of corruption, government effectiveness, political stability and absence of violence, regulatory quality, rule of law, voice and accountability, is a model for development. In this study, the World Bank's assessments and statistics on the six-fold good governance indicators published each year, were used to survey 186 countries worldwide. The aims of this research were studying the status of countries based on good governance and determining the status of Iran among other countries, using clustering technique; And analyzing the trend of Iran's position in the 2021 horizons using time series analysis. Using the clustering method of the countries of the world, based on the good governance and the frequent clustering of Iran with other countries, they were separated. Then, from the time series method using of the exponential smoothing based on the ARIMA's method was investigate to predict the six's good governance indicators and the situation of the country in the next five years. Findings of the research show that in the 2021 horizons, the accountability index will be problematic in the country and the rule of law and control of corruption ratios will remain almost unchanged, and, on the other hand, the rest of the indicators show a slight improvement. Manuscript profile -
Open Access Article
12 - Forecasting of OPEC's Global Crude Oil Demand using Vector Self-Engagement Models, Collective Exploration and Gravitational Search
heshmatolah asgari mohammadreza omidi zahra malekinia ALIAKBAR OMIDIKnowledge about future oil demand is essential for OPEC member countries to set priorities and select policies in order to achieve economic growth and development. So in this study, the OPEC oil demand has been predicted using time series models Including Structural Vec MoreKnowledge about future oil demand is essential for OPEC member countries to set priorities and select policies in order to achieve economic growth and development. So in this study, the OPEC oil demand has been predicted using time series models Including Structural Vector Autoregressive model (SVAR), Autoregressive Integrated Moving Average model (ARIMA) and Gravitational Search Algorithm (That is one of the Innovative Search Algorithms) applying demand data from 1970 to 2014. In this regard, three criteria including Mean Sum of Squared Errors (MSSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) have been used to measure the predictive power of triple models. Results indicate that the SVAR model has the most appropriate prediction of OPEC global demand. According to results of this model, net export variable has a positive and significant impact on oil demand and OPEC petroleum price and non- OPEC production variables have a negative and significant impact on oil demand. Manuscript profile -
Open Access Article
13 - Prediction of Customer Satisfaction level in after-sales service in automotive industry- Dealers in Saipayadak Co.
Reyhaneh Varasteh Ahmad EbrahimiBackground: Based on the competition and product variety in the automotive industry, auto makers require to achieve capability to respond properly to customers and their competitors. The special position of after-sales service in automotive industry and also maintain th MoreBackground: Based on the competition and product variety in the automotive industry, auto makers require to achieve capability to respond properly to customers and their competitors. The special position of after-sales service in automotive industry and also maintain the existing customers and attract the new ones, makes the prediction and measurement of customer satisfaction as a must in this industry.Purpose: In this paper, using prediction approach in futures studies, has made us firstly to identify the influential factors on customer satisfaction. Then the customer satisfaction level has been predicted and analyzed in after-sales service of dealers in an automotive manufacturer.Methods: The statistical population includes the dealers of Saipayadak Co. The statistical sample includes 14486 of after-sales service dealers in the period of April 2017 to June 2017. Independent variables, after extracting through literature review, were finalized using brainstorming and fishbone diagrams. Statistical analysis and prediction was performed using stepwise regression method with coding in RStudio software.Findings: By using data mining method, the customer satisfaction score in after-sales service of dealers in Saipayadak Co. has been predicted with 80% accuracy.Conclusion: By knowing the customer satisfaction level, auto makers can define quality improvement projects and move toward to competitiveness desirably. Manuscript profile -
Open Access Article
14 - Macro analysis of decision making models predicting consumer buying behavior
seyedmohammadhosein mousavi Karimkarim Hamdi hosein vazifehvoustBackground: The duties of university graduates in the field of marketing management are to present a strategic plan with a forward-looking perspective on consumer behavior as a model for empowering marketers and consumers in particular.Purpose: In this research paper, i MoreBackground: The duties of university graduates in the field of marketing management are to present a strategic plan with a forward-looking perspective on consumer behavior as a model for empowering marketers and consumers in particular.Purpose: In this research paper, it is attempted to investigate the models of predicting consumer buying behavior with macro analysis in physical and virtual space. First, the rules and process of purchasing decision models, and then the formulation of a variety of decision models with the prevailing antimatter in the physical and virtual global competitive environment, with the help of interaction and exchange science and information science and technology.Methods: In order to achieve the results of the research, by designing a questionnaire with a statistical population of 346 people and a five-point Likert scale with 5 subscales, also a questionnaire with Cronbach's alpha of 0.754, using SPSS statistical software and two statistical tests. Significance, standardization and appropriate fit of the selected questions model for the factors under investigation were confirmed by the LISREL Confirmatory Factor Analysis indices of 2.22 df / 2x.Results: For this purpose, the data of exploratory factor analysis using chi-square test with significance level of 0.000 and KMO index for sample adequacy is 0.765.Conclusion: By using From equity statistics, And the matrix of agent rotation, two main factors with two-factor behavioral agents, and three-factor stimuli, with more than 63% of the variance were identified and extracted. Manuscript profile -
Open Access Article
15 - Using an approach based on financial forecasting and soft econometrics for the future research of systems behavior
NABI OMIDIToday, forecasting methods based on soft econometrics as well as financial forecasting methods are used in various systems, one of the aspects of using forecasting methods is to use it to predict the behavior of general systems and It is a quote. In this research, using MoreToday, forecasting methods based on soft econometrics as well as financial forecasting methods are used in various systems, one of the aspects of using forecasting methods is to use it to predict the behavior of general systems and It is a quote. In this research, using the statistics of traffic injuries referred to forensic medicine in Golestan province between April 1374 and March 1401, which were referred to forensic medicine in Golestan province, and using artificial neural network, which is one of the most advanced methods of forecasting and future research In the field of health systems, the number of injured people has been predicted for the 12 months ending in 1402. Also, the accuracy of this method has been measured using the average percentage of the absolute value of the error. The results of the research showed that the artificial neural network with 12 inputs, one output and 5 hidden layers is suitable for predicting the injured referred to Golestan forensic medicine,. The predicted values showed that the number of traffic injuries in Golestan province is increasing. Due to the high accuracy of the neural network in this research, this method can be used as a basis for future research in accidents. The upward trend in the number of traffic injuries in Golestan province indicates the need to review decisions in the field of transportation in this province. Manuscript profile -
Open Access Article
16 - Model forecasts for inflation and economic growth rate futures approach and Gray Markov method
Mohammad Reza Yavarzadeh Ebrahim Hajiani Amir NazmiAccurate forecasts with zero error, regardless of the considered area and topics, are very difficult and almost impossible especially in forecasting process, in a very complex environment and through the thick cloud of uncertainties and several driving forces who affect MoreAccurate forecasts with zero error, regardless of the considered area and topics, are very difficult and almost impossible especially in forecasting process, in a very complex environment and through the thick cloud of uncertainties and several driving forces who affected the environment, and data and information used in forecasting have ambiguous and grey characteristics.The studies also confirmed that some international institutes have provided more accurate forecasts of macroeconomic variables of Islamic Republic of Iran. In the present study which was conducted by quantitative study, trying by using real data, secondary analysis and documents methods the error of forecasting four international institutes such as The Business Monitor, The Economy Watch, The International Monetary Fund and The World Bank in the time span of 20 years (1993-2013) has been calculated. And also by using the Gary Markov Method and combined methods presented a new model which has based on statistical analysis it is proven that this model has less deviation and forecast error than the separated forecasts of each mentioned international institute. Finally, it suggests a native and reliable model for the functional and operational use in providing more accurate forecast of Iran macroeconomic variables (economic growth rate and Iran's inflation rate) by two national institutes (Iran Statistical Center and IRI Central Bank). Manuscript profile -
Open Access Article
17 - شناسایی عوامل و ارزیابی تأثیر آنها بر دقت پیش بینی سود و ارتباط آن با نوسانات قیمت سهام شرکت های پذیرفته شده در بورس اوراق بهادار تهران
هاشم نیکو مرام منصور گرکز -
Open Access Article
18 - مقایسه توانایی مدل های آلتمن، اوهلسان و زاوگین در پیش بینی توقف فعالیت شرکت های پذیرفته شده در بورس اوراق بهادار تهران
احمد یعقوب نژاد خالد شیخی -
Open Access Article
19 - An Impirical Investigation of the Effects of Financial Statement Analysis in Predicting Future Dividend of the Firm Member in Tehran Stick Exchange.
R. Shabahang F. HeydarpourPrediction of dividend is an important factor for decision making. Financial statement analysis can used for divided prediction . Decision makers usually co MorePrediction of dividend is an important factor for decision making. Financial statement analysis can used for divided prediction . Decision makers usually consider earnings as a signal for dividend figure . In this research two hypothesis are investigated : 1) There is a relation between financial variables / ratios ( other than earning figure alone ) and dividend and 2) financial variables / ratios are useful for prediction of dividend by using model . For that ,194 firms member in Tehran Stock Exchange were investigated .Methodology of research is correlation . Dependent variable is dividend and independent variables are 24 financial variables / rations . At first , the model was derived by using 1375-1380 data and the it’s fitness was evaluated . 8 variables was remained in model . For more confidence those process were done with 1375-1379 data and dividends of 1380 were predicted . It showed about 75 percent of real dividends in 1380 were between upper / lower limit at 95 percent level . Then the research hypothesis were confirmed . The non – earning / non-dividend variables are debit to total assets , equity . inventory to assets , debit and share price before stockholder’s meeting . Other variables are EPS , ROI , net sales to equity. Manuscript profile -
Open Access Article
20 - The predictive ability and information content of aggregate earnings beyond disaggregate earnings
R. Shabahang Z. LashgariThe predictive ability and explanatory power of an aggregate model of reported earnings is compared to adisaggregated model of reported earnings by examining their associations with contemporaneous stockreturns and future earnings. The change in annual reported earnings MoreThe predictive ability and explanatory power of an aggregate model of reported earnings is compared to adisaggregated model of reported earnings by examining their associations with contemporaneous stockreturns and future earnings. The change in annual reported earnings is disaggregated into changes in revenue,operating margin, and other expenses in order to examine whether they individually and jointly conveyinformation about future earnings that is not reflected in aggregate earnings and whether this incrementalpredictive ability is reflected in security prices.This study contributes to the information content literature in two ways. First, it examines the informationand valuation link between the operating income components of reported earnings and future earnings andstock returns. Second, the empirical analysis is conducted on an industry basis and over a eight-year periodto examine how the predictive ability and information content of earnings and its components vary acrossindustries and over time.The results indicate the following. First, changes in revenue, operating margin, and other expenses (thedisaggregated model) jointly have not predictive ability and information content beyond the change inaggregate reported earnings with respect to one-year ahead annual earnings and contemporaneous annualstock returns. Second, the predictive ability and, information content of these earnings components as well asaggregate earnings varies across industries and varies over time Manuscript profile -
Open Access Article
21 - A review of theoretical foundation and key concepts of futures studies regards to development of implementation framework of Futures Studies
Ardeshir Sayah Mofazali Alireza AsadiFutures studies as an academic field is a new era of social science that concerns a historical issue knowing future, in scientific approach. Futures Studies as a branch of social science has its own paradigms, theories and schools of thoughts that explains future dimens MoreFutures studies as an academic field is a new era of social science that concerns a historical issue knowing future, in scientific approach. Futures Studies as a branch of social science has its own paradigms, theories and schools of thoughts that explains future dimension. During decades many methods and tools has been developed to study trends, emerging issues and events by scholars and professionals. In this paper authors are reviewing the evolution of theoretical foundations of futures studies to explain the key concepts and basis of this era; Including the development of thinking about future of civilization and utopia since the 16th century to the present, differences between prediction and futures study, alternative futures versus single predefined future, dimensions of the future, path dependencies versus future breaking, tools and methods of futures studies. In light of this review, a conceptual framework has been developed to choose appropriate strategy for futures studies research. However without deep understanding and systematic methodology of futures research, applying tools could not meet the complicated needs of societies and organization in face of emerging issues in further new world. Manuscript profile -
Open Access Article
22 - Expanding the Application Models Box Jenkins, Artificial Neural Network and Adjusted Exponential forecasting Social Phenomena (Case study: forecasting of marriage and divorce in Ilam)
Mohammadreza Omidi Nabi Omidi Ardashir Shiri R. MohammadipourOne of the most important tools in the hands of managers and experts to make strategic decisions is Methods of forecasting and futures. Despite the development of prediction methods, but less likely to use these methods in predicting social phenomena such as marriage, MoreOne of the most important tools in the hands of managers and experts to make strategic decisions is Methods of forecasting and futures. Despite the development of prediction methods, but less likely to use these methods in predicting social phenomena such as marriage, divorce and population growth are discussed. In this study, using data from marriage and divorce between the years 1992 to 2013 in Ilam province to forecasts, the number of these phenomena using models Box Jenkins, Artificial Neural Network and Adjusted Exponential has been studied for years to come. The results showed that the prediction accuracy Box Jenkins model to predict the number of marriages and Artificial Neural Network model to predict the number of divorces is more than any other prediction methods. The predicted values showed that the proportion of marriages end in divorce in Ilam province between the years 2014 to 2018 following the gentle slope, to reduce the move. Manuscript profile -
Open Access Article
23 - Investigation of Immigration to Tehran Using Causal Layered Analysis (CLA)
Aliollah GhanbariTehran's population growth and the entry of new immigrants has been one of the problems for governors, policy makers, and planners. Therefore, since the middle decades of the current century, as a concern, it has been considered as a threat to social, environmental, hea MoreTehran's population growth and the entry of new immigrants has been one of the problems for governors, policy makers, and planners. Therefore, since the middle decades of the current century, as a concern, it has been considered as a threat to social, environmental, health, and disaster preparedness issues. However, the activities have been performed to prevent Tehran population growth, failed to achieve success and in spite of all these activities, the problem of Tehran population and immigration growth still exists.In this paper, causal layered analysis (CLA) as a futures study method is used for splitting and analyzing the several layers leading to the issue of Tehran immigration growth, and different scenarios are considered for the future. In this regard, based on analysis of the under layers and due to the uncertainty and importance, "development model" and "cultural orientation" are identified as its drivers and the scenarios are designed according to them. Manuscript profile -
Open Access Article
24 - Expanding the Application Models Box Jenkins, Artificial Neural Network and Adjusted Exponential forecasting Social Phenomena (Case study: forecasting of marriage and divorce in Ilam)
Mohammadreza Omidi Nabi Omidi Ardeshir Shiri Rahmatullah MohammadipourOne of the most important tools in the hands of managers and experts to make strategic decisions is Methods of forecasting and futures. Despite the development of prediction methods, but less likely to use these methods in predicting social phenomena such as marriage, d MoreOne of the most important tools in the hands of managers and experts to make strategic decisions is Methods of forecasting and futures. Despite the development of prediction methods, but less likely to use these methods in predicting social phenomena such as marriage, divorce and population growth are discussed. In this study, using data from marriage and divorce between the years 1992 to 2013 in Ilam province to forecasts, the number of these phenomena using models Box Jenkins, Artificial Neural Network and Adjusted Exponential has been studied for years to come. The results showed that the prediction accuracy Box Jenkins model to predict the number of marriages and Artificial Neural Network model to predict the number of divorces is more than any other prediction methods. The predicted values showed that the proportion of marriages end in divorce in Ilam province between the years 2014 to 2018 following the gentle slope, to reduce the move. Manuscript profile -
Open Access Article
25 - Financial Market Forecasting Methods under Structural Break
Frozandeh Jafarzadehpour Amir Nazemy Alireza AsadieFinancial market forecasting particularly stock market forecasting is a considerable debate that confront to forecast failure and model break down when structural breaks in trends occur. This paper discusses the modeling to predict stock return under structural br MoreFinancial market forecasting particularly stock market forecasting is a considerable debate that confront to forecast failure and model break down when structural breaks in trends occur. This paper discusses the modeling to predict stock return under structural breaks and investigate new approaches of forecasting in this condition. This study proposes a taxonomy for research area in forecasting under structural breaks to suggest further studies. We use literature survey as methodology of the research and categorizes the methods, models, and results of the recent researches in stock market forecasting. Consequently, it provides three categories of strategies to forecast stock return under structural breaks. First strategy, called economically motivated model restrictions, uses financial theories as signs to adjust the parameters of models in out-sample periods. Second strategy, known as regime shift, uses a Markov chain transition matrix to model structural breaks in time series. Third strategy applies mix of quantitative models and qualitative surveys to predict future of financial markets. The proposed strategies are applicable in Tehran stock exchange under uncertainty conditions. Manuscript profile -
Open Access Article
26 - Forecast of cash flows in the listed firms of Tehran Stock Exchange
Rasoul Yarifard Jafar Karmanj Hossein Nematjoo Mahdi EbrahimiForecasts of cash flows are considered by investors, creditors,firm employees and rating institutions. Investors regard cash flows as the input of their investment models allowing them to make decisions about returns resulted from the divided profit and capital. Credito MoreForecasts of cash flows are considered by investors, creditors,firm employees and rating institutions. Investors regard cash flows as the input of their investment models allowing them to make decisions about returns resulted from the divided profit and capital. Creditors are interested in the decisions of paying the firm obligations exchanging with them and the employees are concerned with cash flows in terms of job security and persistence of activities of firm that they are working there. Persistence of activity and the firm ability in timely payment of debts are also highly important for rating institutions. The main purpose of the present study is the investigation of forecasting cash flows among 97 firms from the listed firms of Tehran Stock Exchange from the beginning of 1388 to the end of 1392.To investigate the research hypotheses, it was used from panel data regression model. The results showed that the costs of sold goods and the public and administrative costs have significant impacts on forecasting cash flows, however, sales, change in the payable accounts, change in the receivable accounts, change in inventory, tax and cash flows of the last year have not significant impacts on forecasting cash flows. Manuscript profile -
Open Access Article
27 - Bankruptcy Prediction Using Artifical Neural Networks with Camparsion to the Altman Model
M.R. Setayesh D. Ahadianpoor ParvinThis research has been done under title: Bankruptcy Prediction using Artificsl Neural Networks withcamparsion to the Altman Model.The goal of this study is to provide exact explanation and presentation of theoretical basis of research andmeasurement of usefulness bankru MoreThis research has been done under title: Bankruptcy Prediction using Artificsl Neural Networks withcamparsion to the Altman Model.The goal of this study is to provide exact explanation and presentation of theoretical basis of research andmeasurement of usefulness bankruptcy financial models. We presented the research hypotheses in order toprovide suitable scientific context for the study.Hypothese 1: Artificsl Neural Networks and Altman models are suitable instrumental for prediction ofbankruptcy.Hypothese 2: In prediction of bankruptcy one firm, have significant difference the resultsof this two models.The means of the research statements (Balance sheets, Income statement, cash flow statement) of thecompanies which were accepted in Tehran Stock Exchange. The library method was employed in datagathering. Statistical population of research includes active companies whose financial statements areaccessable in Tehran Stock Exchange. The statistical sample of the research includes active companies inproductive industries, from 1379 to 1384.In order to analysis data, We used statistical metods of nonparametric binomial, and for cointegrationsignificant difference two models employed wilcoxon signed- rank test and sign test for hypothese 2. Afteranalyzing the data the results gained id confirmed and supported by above tests Manuscript profile -
Open Access Article
28 - The Application of Altman & Springate Models In Bankruptcy Prediction of Accepted Companies In Tehran Stock Exchange
A. Mohammadzadeh M. NoferestiThe investors are always trying to prevent from losing their capital ad interest through predicting theprobability of the bankruptcy of a Company since in the event of the bankruptcy, value of thesecurities decreases intensely. So, the investors are looking for methods MoreThe investors are always trying to prevent from losing their capital ad interest through predicting theprobability of the bankruptcy of a Company since in the event of the bankruptcy, value of thesecurities decreases intensely. So, the investors are looking for methods by which they could predictthe bankruptcy of the Companies. Moreover, one of the issues discussed 'in financial management isthe investment and trust in the investment and one of the things that could help the investors to makeright decisions in their investments is the existence of some tools and models for the assessmenl offinancial status and the condition of the Organizations.The purpose behind this research is to determine the efficiency of Altman and Springate Models inpredicting the bankruptcy of a Company. The statistic Community on which this research was 'madeis~ the successful and bankrupted Companies in Tehran's Security Exchange and the required Data tomake this research is collected in a period of five years (2001-2006). After calculating the ratiosexistent in the models and determining z index, accuracy and error for each of the models arecalculated .Regarding the results obtained from the, research, both, of Altman and Springate Models have thecapability to predict 'the bankruptcy of the Companies in Tehran's security Exchange while AltmanModel enjoys from more accuracy in comparison with Springate Model. So, the prospective investors,shareholders and others are recommended to use Altman Model in predicting the bankruptcy of theCompanies accepted in Tehran 's Security Exchange. Manuscript profile -
Open Access Article
29 - A Review Of Cross Impact Analysis Methods And An Introduction To the Correlation Logic Method
Ebrahim Hajiani Alireza HemmatiMost of the futures study methods evaluate the concerning variables and drivers seperately to predict or examine the events. However, some times there is a need to analyze the event occurance probability in correlation with a series of predicted events. The Cross Impact MoreMost of the futures study methods evaluate the concerning variables and drivers seperately to predict or examine the events. However, some times there is a need to analyze the event occurance probability in correlation with a series of predicted events. The Cross Impact Analysis method is the key to this problem. Requiring more complex statistical processing to achieve the results, the Cross Impact Analysis method, like the Delphi method, is based on the experts opinions. The main approach in this method is to determine the event occurance probability or various driver forces seperately and ask the experts opinions for the event occurance probability in case of other event occurances and their cross impact. In advanced methods of this analysis, discussed in this study, event occurance probability is reviewed in the chain of reasons between events. Thus, a matrix of the primary probabilities and conditional probabilities and directed event cross impact relations and driving forces is designed. The common methods of this analysis defines rules based on the two logic of probabilities and structures relations for the events impacts on each other. However, both methods are not used for the cross impacts. In this study, authors presented a new method of correlation logic to cover both positive and negative impacts of events on each other using a review on available methods of cross impact analysis. Cross impact analysis method usually leads to a scenario Manuscript profile -
Open Access Article
30 - Modeling and forecasting electricity production and Consumption in Iran
Mohammadreza Omidi Nabi Omidi Heshmatolah Asgari Meysam Jafari EskandariDue to the relatively high growth of energy consumption in the country, the future of research in the field of electrical energy as an important intermediate inputs in industrial production and as a final good And the necessary domestic and commercial sector, the requir MoreDue to the relatively high growth of energy consumption in the country, the future of research in the field of electrical energy as an important intermediate inputs in industrial production and as a final good And the necessary domestic and commercial sector, the requirements of law enforcement agencies in the field of production and consumption of electricity. Review and forecast electricity consumption and production managers a valuable factor in the power industry for strategic decision making. In this study, using time-series production and power consumption between the years 1967-2013 and deployment of predictive models Box Jenkins, artificial neural network and gray system in addition to the forecasts for the coming years using the standard average percentage of errors the accuracy of prediction methods were also studied villages. The results showed that the highest accuracy in the prediction of Box Jenkins methods and artificial neural network to predict the power consumption is the highest accuracy. The predicted values showed a decreasing ratio of production to consumption in Iran is relatively constant desire and The electricity production in Iran in 2019 to 318 843 million kW per hour and power consumption to be 260,645 million kWh, Which can be modified using modern methods of production and consumption patterns towards increased production to consumption. Manuscript profile -
Open Access Article
31 - Using a Modified Trainable Neural Network Ensemble for Trend Prediction of Tehran Stock Exchange (Case Study: Kharg Petrochemical Company)
A. Shahrabadi R. Ebrahimpour H. NikooThis paper represents a comparison between modified trainable neural network ensemble with othertrainable and non-trainable ensembles. The historical data available in this case study are from khargpetrochemical company in Tehran stock exchange. This company is one of t MoreThis paper represents a comparison between modified trainable neural network ensemble with othertrainable and non-trainable ensembles. The historical data available in this case study are from khargpetrochemical company in Tehran stock exchange. This company is one of the biggest producers ofpetrochemicals, including methanol, in Iran and its stock price is very much dependent on worldmethanol price. Therefore Kharg stock price reflects its financial information more clearly than otherswith no products for global exportation. The reason of choosing Kharg is related to its large datahistory and high rate of stock free float1. The results show how a modified trainable neural networkensemble can overcome other trainable and non-trainable ensembles. This study also demonstrateshow we can beat the market through our proposed model without the use of extensive market data orknowledge Manuscript profile -
Open Access Article
32 - Identification and ranking the factors affecting organizational cynicism and its implications with the Analytic Hierarchy Process (AHP): (A Study among faculty members)
seyedeh laya mortazavi ابوالحسن فقیهیBackground:One of the problems that now threat organizations and is one of the challenges of management is organizational cynicism.Objective:In this paper, the causes of organizational cynicism among faculty members and their implications have been identified.Methods: A MoreBackground:One of the problems that now threat organizations and is one of the challenges of management is organizational cynicism.Objective:In this paper, the causes of organizational cynicism among faculty members and their implications have been identified.Methods: After reviewing the literature and interviews with 15 experts, using AHP technique to identify and rank the most important reason was the organizational cynicism and its consequences.Results: Of the 19 factors were identified: perception of organizational policy , social cynicism, psychological cynicism, breach of contract , reducing organizational justice , reducing organizational support , job security and style of leadership. 8 also factor as to the consequences of the spread of this phenomenon at the University of 4 were identified by their important factor of experts respectively: obsessing over organizational change , reducing organizational commitment , reducing the incidence of organizational citizenship behaviors and reduction of job satisfaction. Conclusion: The findings suggest that universities consider the factors in the creation of organizational cynicism and control of the spread of this phenomenon avoid the consequences Manuscript profile -
Open Access Article
33 - Effect Of Managers' Behavioral policy On Abnormal Transactions With Affiliates
nazanin bashirimanesh zohreh arefmanesh mohammad souriBackground: The main role of managers in companies is to make decisions in various areas such as investment, profit sharing policy, transactions with affiliates. One of the factors influencing managers' decision-making approaches is their behavioral policy.Objective: Th MoreBackground: The main role of managers in companies is to make decisions in various areas such as investment, profit sharing policy, transactions with affiliates. One of the factors influencing managers' decision-making approaches is their behavioral policy.Objective: The present study investigates the effect of managers' behavioral bias on abnormal transactions with affiliates.Methods: The statistical population of the study is the companies listed on the Tehran Stock Exchange and using the systematic elimination sampling method, 146 companies were selected as the sample of the research in a period of 7 years between 1392 to 1398. The method used to collect information is a library and the relevant data for measuring variables were collected from the Cadal site and companies' financial statements and in Excel preliminary calculations were performed and then Stata software was used to test the research hypotheses.Findings: The results show that managers' narcissism has a significant inverse effect on abnormal net credit and abnormal net sales. However, managers' overconfidence has a direct and significant effect on abnormal net worth and abnormal net sales. Also, managers' shortsightedness has a direct and significant effect on abnormal net credit and abnormal net sales.Conclusion: Transactions with affiliates allow the exchange of resources, services, or liabilities with individuals such as major shareholders, affiliates, and subsidiaries. Therefore, the behavioral policy of managers affects the use of transactions with affiliates in order to achieve personal goals or promote profitability. Manuscript profile -
Open Access Article
34 - Designing and Testing the Organizational Pessimism Pattern by Ethnography Approach (Case Study: Esfahan Province Electricity Distribution Companies)
Hossein sadri Mohammad Reza Dalvi Ali Reza ShirvanyIn current age,one of the serious challenges facing managers is the organizational pessimism phenomenon and considered by many organizations. The purpose of this research is to identify the effective factors , consequences and design the native pattern of organizationa MoreIn current age,one of the serious challenges facing managers is the organizational pessimism phenomenon and considered by many organizations. The purpose of this research is to identify the effective factors , consequences and design the native pattern of organizational pessimism in the companies studied. This research is in terms of purpose, is developmental and in terms of nature is scrolling. The method of research is done in two sections, quality and quantity .In the qualitative section, using the ethnographic method, the causative factors and the consequences of organizational pessimism, the identification and analysis of the data through the thematic analysis and the design of the conceptual model was carried out. In the quantitative part and using the abstract ladder, the research questionnaire was adjusted the effect of each of the variables identified in the qualitative section was tested. The statistical population of the research is the personnel of the electricity distribution companies in the province of Isfahan. For sampling according to the Cochran formula, 360 individuals were selected .. The validity of the questionnaire was confirmed by using structural equation model and reliability by Cronbach's alpha.. The results show that individual, group, organizational and environmental factors affect organizational pessimism . Manuscript profile -
Open Access Article
35 - پیش بینی فروش فیلم های سینمایی در ایران با استفاده از شبکه های عصبی و مقایسه آن با روش های آماری
عباس طلوعی اشلقی عباس سقایی سارا خورسندی کریمی -
Open Access Article
36 - Analysis of Factors Affecting the Improvement of Quality of the Environment of Residential Complexes (Case Study: Vahdat Beton Complex of Sadra Town)
Sudabeh Mohammadzadeh Ali Reza Einifar Hamid MajediThe first thing that comes to mind when residential areas in the culture of contemporary Iranian architecture are studied is that achieving higher quality in residential environments is a necessity given the said point. Identifying the main factors that affect quality i MoreThe first thing that comes to mind when residential areas in the culture of contemporary Iranian architecture are studied is that achieving higher quality in residential environments is a necessity given the said point. Identifying the main factors that affect quality improvement, providing a model for quality measurement in the residential environment, and then prioritizing indexes is essential. Not only does this method study the issue of quality from the perspective of residents living in the selected complex, but also it can be used in quality improvement policies and strategies of residential environments. Therefore, this article considers three main factors: capability of intermediate spaces, quality of architectural design, and personal characteristics of residents in question. This article analyzed the relationship between these factors and the quality of residential complexes. Further, it determined environmental quality based on residents’ needs and expectations by providing a four-level model for measuring quality in residential complexes and measuring indicators from residents. Then, it identified the principal indicators in quality improvement of the environment by prioritizing indicators. This measurement used t-test, correlation, and factor analysis. The results obtained in the field of research hypotheses showed that there is a significant correlation between the indicators of the duration of residence, level of education, age and type of ownership (in the individual characteristics of residents), the ability of intermediate spaces, and the quality of architects’ design with the quality of the residential environment. The results showed that the residents of Vahdat Beton Complex are not satisfied with the quality of their residential environment. The quality score showed that the most dissatisfaction is with the area of the residential complex. Also, the consequence of the significant coefficient demonstrated that the area of the residential unit should be considered by the city officials, as their top priority. The results of the analysis of the elements that make up the quality of the environment showed that space 2 at the level of the neighborhood unit, space 2 at the level of the residential complex, and space 3 at the level of the residential unit is more important spaces for the residents. Moreover, the lowest level of residents’ satisfaction is with the accessibility at the level of the residential complex and the observance of privacy, overlooking, and visual pleasure at the level of the residential unit. Prioritization of measures to improve the quality of the environment showed that space 3, at the level of the neighborhood unit, space 2 at the level of a residential complex, spaces 1 & 3 at the level of the residential unit are the most important spaces for improving the quality of buildings. It also showed that indicators of green space and social livelihood in space 2, visual pleasure and sensual richness in space 3 of neighborhood unit level, accessibility, and readability in space3, green space and controlling the entry of strangers to the complex in space 1 of residential complex level, green space, and belonging in space 3, privacy and overlooking in space 1 of the residential unit level. Manuscript profile -
Open Access Article
37 - The Role of In-Between Spaces to Identifying Historical Fabrics of Iranian Cities
Lida Balilan Asl Iraj Etesam, Seyed Gholamreza IslamiLida Balilan Asl (Email:lidabalilan@iaut.ac.ir) , Ph.D, Department of Art and Architecture, Science and Research Branch, Islamic Azad University, Tehran, Iran. Iraj Etesam,Ph.D, Professor, Faculty of Architecture, University of Tehran. Seyed Gholamreza Islami,Ph.D, As MoreLida Balilan Asl (Email:lidabalilan@iaut.ac.ir) , Ph.D, Department of Art and Architecture, Science and Research Branch, Islamic Azad University, Tehran, Iran. Iraj Etesam,Ph.D, Professor, Faculty of Architecture, University of Tehran. Seyed Gholamreza Islami,Ph.D, Assistant Professor, Faculty of Architecture, University of Tehran. The research and topical purpose of this thesis is first to determine the characteristics of in-between space, then to recognize these spaces in the context of the architecture and finally to identify their role in the spatial organization of urban and architectural elements. One of the major problems in the fabric of most cities in the world, is the crisis in the identity of urban and architecture. The physical display of the identify crisis in the cities is the spatial separation of the architectural and urban elements, in the particular and whole scales. As to the claim of this thesis, an ignorance of the connective and in-between spaces is an important and impressive factor in the physical identity crisis of the historical fabrics. To obtain the mentioned objectives and to prove the hypothesis of the thesis, a phenomenological approach and historical analysis method are used to analyze the content of the texts. The theoretical basis of the thesis is founded on the researches on the various aspects of the space and on the concepts which are influential on setting limiting borders and defining the architectural spaces and consequently the in-between spaces which are analyzed according to the structural content analysis as well as analysis-comparison. Due to its nature, the in-between space has some various spatial and meaningful characteristics. This quality has caused the in-between characteristics to be expressed in terms of three forms of formal-physical, meaning-functional and connective-geometrical. Therefore, the relation and interaction of the functions require a third space between the interior and exterior spaces (in & out). Moreover the conceptual focus, the functional interaction and the formal distinguish, imply a fencing of the interior space through a threshold which allows a relation and connection with the outer space. This threshold not only determines and controls the domain and ownership, but it also plays the role of reception, interpretation, improvise and change of the information. The threshold as a distinguishing, connecting and relating factor through the transition field, intervenes in the space organization. This impact can well be observed through determining of the formation features and elements, the pattern of relationship and the discipline dominant over the relations in terms of some organizational principles such as spatial hierarchy. The obtained results suggest that the in-between space due to its constructive objectives takes on an equivocal nature. It becomes both the process and the product. Thus, it contributes to the formation process in order that a unified whole should emerge; it also helps simultaneously the concepts be classified and take orientation. Therefore, in a rotational movement the in-between space influences the spatial organization through its impact on the basics and principles. On the other hand, through its spatial features such as space relations, the spatial organization is influential in the development and evolution of the in-between spaces. The result emphasizes on the comprehensibility of the in-between spaces in the various urban and architectural scales, and consequently it puts emphasis on the significance of the in-between spaces as the major factors in the spatial organization. Manuscript profile -
Open Access Article
38 - Designing a smart algorithm for determining stock exchange signals by data mining
pantea maleki-moghadam akbar alem-tabriz esmael najafiOne of the most important problems in modern finance is finding efficient ways to summarize and visualize the stock exchange market. This research proposes a smart algorithm by means of valuable big data that is generated by stock exchange market and different kinds of MoreOne of the most important problems in modern finance is finding efficient ways to summarize and visualize the stock exchange market. This research proposes a smart algorithm by means of valuable big data that is generated by stock exchange market and different kinds of methodology to present a smart model.In this paper, we investigate relationships between the data and access to their latent information with an enormous amount of data which has a significant impact on the investor’s decisions. First, extracting technical indicators from different point of the charts based on two groups of stock exchanges like petrochemical and automotive during 1387 to 1396, then analyzing clusters by means of k-means algorithm and data mining methodology. The contributions of this paper are: 1. To create a model with twenty technical indicators in different stock exchange companies and industries.2. To evaluate the proposed model and finally to predict the sales signals at the maximum points which has significant performance and can be predicted with acceptable accuracy. Manuscript profile -
Open Access Article
39 - Presenting a model for predicting the Tehran Stock Exchange Index using ANFIS and fuzzy regression
Mohammad Hossein Keshavarz Mohammad Reza Feylizadeh Ayad HendalianpourThe purpose of this study is to provide a prediction model for the Tehran Stock Exchange Index using Adaptive Neuro-Fuzzy Inference System (ANFIS) and fuzzy regression analysis. The behavior of this index is nonlinear and chaotic that traditional methods do not predict MoreThe purpose of this study is to provide a prediction model for the Tehran Stock Exchange Index using Adaptive Neuro-Fuzzy Inference System (ANFIS) and fuzzy regression analysis. The behavior of this index is nonlinear and chaotic that traditional methods do not predict accurately. Hence, using the above two tools and identifying three macroeconomic variables including inflation rate, exchange rate and crude oil price as independent variables, we predicted the index of the total stock index for the next week. Then, the modeling was performed using the above three variables. By comparing the results, ANFIS performance was better than fuzzy regression. The Root Mean Square Error Performance criterion was obtained for the ANFIS output of 0.021248. The prediction of the next week showed an error reduction for both tools and ANFIS again with an error value of 0.007933, yielded superior performance of the study. Also, the model with four inputs was more accurate compared to the model with three inputs. The emphasis on using macroeconomic variables, predicting the next week's index number, using the two tools mentioned, analyzing the sensitivity of the models during the research are the characteristics of this research. This research can be used by all companies in the stock exchange, investors, brokers, and individuals and legal entities dealing in any way with the stock market. Manuscript profile -
Open Access Article
40 - حق فسخ ناشی از پیشبینی نقض قرارداد در اصول قراردادهای تجاری بینالمللی، کنوانسیون بیع بینالمللی کالا و حقوق ایران
رسول قاسمی محمد هادی مهدوی -
Open Access Article
41 - Modeling and Forecasting Distribution of Return on the Tehran Stock Exchange Index and Bitcoin with the GAS Time Variable Method
Mohammad Ebrahim Samavi hashem nikoomaram Mahdi Madanchi Zaj Ahmad YaghobnezahdPredicting returns with the least error is one of the most important issues in financial markets that has been considered by many researchers in recent decades .Traditional linear and nonlinear models due to the inefficiency of linear models in market turbulence, the la MorePredicting returns with the least error is one of the most important issues in financial markets that has been considered by many researchers in recent decades .Traditional linear and nonlinear models due to the inefficiency of linear models in market turbulence, the lack of correct extraction of the conditional distribution form of data due to the failure to record the conditional distribution dynamics in nonlinear models and the existence of limiting assumptions, it lacks the ability to predict returns in different market conditions. In order to eliminate the disadvantages of traditional models, in the present study using a new time-variable method called generalized autoregressive score (GAS) in order to predict the distribution of return of the total index of the stock exchange during the period 2010 to 2020 and for Bitcoin during the period 2014 to 2020. The results of modeling for the two assets by the new GAS model are compared with the results of the GARCH and AR models and their performance is tested for inside and outside the sample. The results show that in order to predict the daily return, the overall index of the new GAS model has a better performance and in order to predict the daily return of bitcoin, the GARCH model has been preferred. Manuscript profile -
Open Access Article
42 - Forecasting of Banks Liquidity resources
Dr.Ahmad Yazdanpanah Zahra AbbasiLiquidity management is one of the most important functions of financialmanagement in economic firms. In the case of financial and creditinstitutions especially banks, it has a more important role. Banks requireto maintain a portion of their assets in the form of cash i MoreLiquidity management is one of the most important functions of financialmanagement in economic firms. In the case of financial and creditinstitutions especially banks, it has a more important role. Banks requireto maintain a portion of their assets in the form of cash in order to be ableto respond to their customer’s needs. However, it has an opportunity costfor the bank. In other words, keeping cash in current accounts ormaintaining it by Central Bank or other banks decreases the risk of bankliquidity while it deprives banks of investment opportunities and declinesthe bank returns.In this study, therefore, we tried to design a model in order to forecast thecash amounts of EN-Bank kept in current accounts or maintained byCentral Bank or other banks which is totally called “Bank Liquidity”.Thus, forecast was done based on input cash flow during a specificperiod. Then by comparing this with the goals and strategies of the bank,it has been planned to eliminate the budget deficit or surplus consumptionin order to reach the equilibrium at the end of the period. In this method,current accounts, interbank accounts and funds are considered asliquidity. ARIMA and Minitab software are used in order to estimate themodel.At the end, forecast was done for the next 52 weeks by this model. As aresult, it was observed that bank will be faced surplus liquidity Manuscript profile -
Open Access Article
43 - Forecasting the Price of Natural Gas Using Developed Methods Based on Grays and Fractals
Saeed Emami Koupaee Shiva Zamani A. Reza Heidarzadeh Hanzaee M. Reza ShahnazariThe importance of predicting the price of energy carriers for the development of the economy and industry today is not overlooked. Meanwhile, predicting natural gas prices as one of the most important carriers of energy and an important role in providing clean energy ca MoreThe importance of predicting the price of energy carriers for the development of the economy and industry today is not overlooked. Meanwhile, predicting natural gas prices as one of the most important carriers of energy and an important role in providing clean energy can be considered as an important tool in industrial development decision making. In this paper, we have investigated the nonlinear behavior of natural gas prices in a multi-year period, as well we have introduced methods for the development and synthesis of fractalization (FDGM) has been used to predict the price of natural gas. The results of the price forecast based on the introduced methods, Indicates the effectiveness of these methods. At the same time, given the fractal nature of the price of natural gas in the period under review, the results show that the forecast error using the FDGM method is always below 7%. And very good results were obtained using combination fractional and fractional methods. Manuscript profile -
Open Access Article
44 - The Impact of Investor and Managers' Behavioral Bias on the Stock Price Bubble in capital market of Iran
nazanin bashirimanesh shahnazi hosseinIn emerging capital markets, the inability of investors to analyze financial information, scarcity of information, as well as the impact of macroeconomic and political factors on financial markets, causes the investor to focus on market excitement and the behavior of ot MoreIn emerging capital markets, the inability of investors to analyze financial information, scarcity of information, as well as the impact of macroeconomic and political factors on financial markets, causes the investor to focus on market excitement and the behavior of other investors. The emotional and herd behaviors of investors are the source of the emergence of various anomalies such as price bubbles and the formation of sharp fluctuations in the market. Managers also have behavioral biases such as overconfidence, myopia and narcissism, which leads to a favorable image of the business and delays in presenting bad news, resulting in stock price bubbles. Accordingly, the purpose of this study is to investigate the effect of biases of investors and managers' behavior on the stock price bubble. The research sample included 129 companies listed on the Tehran Stock Exchange in the period 1392 to 398.To test the hypotheses, multivariate regression method with combined data was used.The results show that investors' behavioral distortions (emotional and herd behavior) increase the gap between the intrinsic stock price of the company and its value set by investors and lead to the formation of stock price bubbles. Managers' behavioral biases (overconfidence myopia and narcissism) also lead to the emergence of stock price bubbles. Manuscript profile -
Open Access Article
45 - Forecasts of financial turmoil in Tehran Stock Exchange member banks
مریم خلیلی عراقی کامبیز پیکارجو لیلا جرّاحیIn this research, we assessed the extent to which stock market information can beused to predict leading indicators of the bank financial distress.Likewise, we specified and tested a logit early warning model of bank financialdistress, designed for Iranian banks, which MoreIn this research, we assessed the extent to which stock market information can beused to predict leading indicators of the bank financial distress.Likewise, we specified and tested a logit early warning model of bank financialdistress, designed for Iranian banks, which tests if market-based indicators addpredictive value to models relying on accounting data obtained from stock market.On the other hand, we studied the robustness of the link between marketinformation and financial downgrading of a bank in the light of the safely net andasymmetric information hypotheses. In the end, we concluded that some of the resultsof accomplished studies, support the use of market-related indicators in order topredict the financial distress.Other results, however, show that the accuracy of the predictive power of thefinancial distress depends on the extent to which bank liabilities are market traded. Itmeans that if the bank undertakes to offer accurate data to the market, then a muchbetter prediction can be made based on the bank data. Manuscript profile -
Open Access Article
46 - A framework for measuring and predicting system risk with the conditional value at risk approach
Ja'far Baba Jani M. Taghi Taghavi Fard Amin GhazaliIn recent years with the increasing integration and innovation in financial markets, concerns about the overall stability of the financial system has increased and the concept of systemic risk has become more important. systemic risk is the risk imposed by interlinkages MoreIn recent years with the increasing integration and innovation in financial markets, concerns about the overall stability of the financial system has increased and the concept of systemic risk has become more important. systemic risk is the risk imposed by interlinkages and interdependencies in a system or market, where the failure of a single entity or cluster of entities can cause a crisis in the entire system or market. In this study, we presented a framework for measuring and predicting systemic risk in the capital market of Iran using conditional value at risk approach (CoVaR). On this basis, ΔCoVaR as a measure of systematic risk using quintile regression based on a set of state variables that indicates changes in the distribution of asset returns has been estimated. As well as to enhance the accuracy of the estimate, the research variables modeled after the conditional autoregressive value at risk model (CAViaR) has been developed and some Lagged firm specific characteristic has also been added. In order to test the validity of the model back testing methods have been used. On the other hand, The potential for systemic risk increases when volatility decreases (volatility paradox). In this study, we try to predict systemic risk by take advantage of the panel structure of the data and the relationship between ΔCoVaR and firm-specific variables that are available in certain sections. Manuscript profile -
Open Access Article
47 - Information Flow and Stock Return Predictability
Mohammad Rahimi Abolfazl ShahabadiThis study explores the role of information flow in stock return predictability in Iranian stock market. The empirically motivated models estimated using the monthly data of the Tehran Stock Exchange (TSE) for the period of 2001:01 to 2011:12. While Iranian stock market MoreThis study explores the role of information flow in stock return predictability in Iranian stock market. The empirically motivated models estimated using the monthly data of the Tehran Stock Exchange (TSE) for the period of 2001:01 to 2011:12. While Iranian stock market return is high predictable, the source of return predictability is shown to vary considerably with information flow. The results show that the relevance of the first-order autocorrelation decreases with volatility and reversely, the relevance of a conditional multifactor asset pricing model increases with volatility in this market. Furthermore, the results indicating that the local market risk and changes in oil price affect the expected aggregate return in periods of high information. Manuscript profile -
Open Access Article
48 - Combined Application of State Space in ARIMA Form Model and Monte Carlo Simulation Method to Forecast TEPIX Index
Aghigh Farhadi Farhad GhaffariIn this study, we estimated the parameters using the State Space model described inARIMA form. We’ve also used the Monte Carlo Method for simulating the process in10000 reputations. Then the estimated parameters and the Monte Carlo simulationmethod are used to for MoreIn this study, we estimated the parameters using the State Space model described inARIMA form. We’ve also used the Monte Carlo Method for simulating the process in10000 reputations. Then the estimated parameters and the Monte Carlo simulationmethod are used to forecast TEPIX index, including 739 observations as an in-sampledata from 21th of January 2011 to 19th February 2014 and 59 observations from 20thFebruary 2014 to 21th May 2014 as an out of sample data . Furthermore, For moreinvestigation we’ve considered different horizons of forecasting, short-term (equal to 1week), mid-term (equal to 1 month) and long term (equal to 3 month). The results showedthat Tehran stock market data has enough efficiency to forecast them, and showed that theState Space in Form ARIMA model and the Monte Carlo simulation method can be usedas a predictive algorithm for TEPIX index and other indices with similar nature. Manuscript profile -
Open Access Article
49 - Investigation of Multifractaly Models in Finance
Fraydoon R. Roodposhti Mahdeyeh Klantari DehaghiSpecifying the governing process of stock market’s return with the goal of making optimal decisions and reducing the risk cost has a great importance for investors and policy makers. The importance of market analysis on one hand and the effort for comprehending th MoreSpecifying the governing process of stock market’s return with the goal of making optimal decisions and reducing the risk cost has a great importance for investors and policy makers. The importance of market analysis on one hand and the effort for comprehending the markets on the other hand resulted in that, after the assumptions of efficient market were challenged and universal financial facts such as “fat tails” and “volatility clustering” were discovered, analysts leaned toward multifractaly and Lévy models and moved away from models with random characteristics and normal distribution. This caused multifractal models to be used in different segments of the market. In this article the multifractal approach that in recent years has been used for forecasting and modeling volatility, will be examined. In the beginning the origin of this approach that stems from turbulent flows in statistic physic will be introduced and in the following sections the details about the specifications and features of multifractal time series models, available approaches for estimating them and empirical uses of this model will be mentioned. The results of this research show that the dynamic nature of capital market has caused the approaches, methods and models of market analysis to be permanently changing. In addition, for volatility clustering of time series, smaller scales are considered. Manuscript profile -
Open Access Article
50 - The effect of Overconfidence on Investors Behaviors: Evidences from Tehran Stock Exchange
S. Morteza Mousavi M. Ebrahim AghababaeiIn its most basic form, overconfidence can be summarized as unwarranted faith in one’s intuitive reasoning, judgments, and cognitive abilities .The objective of this study is to examine the effects of this important bias on decisions of investors. Here, besides me MoreIn its most basic form, overconfidence can be summarized as unwarranted faith in one’s intuitive reasoning, judgments, and cognitive abilities .The objective of this study is to examine the effects of this important bias on decisions of investors. Here, besides measuring various aspects of overconfidence(mis calibration, illusion of control, optimism about future, better than average effect, volatility estimation), the relation between individual overconfidence aspects and three performance measures including trading volume of individual investors, number of orders and individual returnhas been tested. The result shows correlation coefficient of 0.747 with99 percent confidence level between overconfidence and number of orders. Also correlation coefficient of 0.695 with99 percent confidence level exists between overconfidence and order volume and finally more overconfidence does not result in more individual returns. Manuscript profile -
Open Access Article
51 - The Relation between Characteristics of Predicted Earnings per Share by Management and Risk and Firm Value in Terms of Future Decision-Making
فرزانه حیدرپور زیبا خواجه محمودAbstractThe firms that have provided a clear picture of their future are more widely acceptedin the market. One of the ways to draw this picture is exposing the prediction of earningper share. This broadcast makes the capital market sure that firm provides informationim MoreAbstractThe firms that have provided a clear picture of their future are more widely acceptedin the market. One of the ways to draw this picture is exposing the prediction of earningper share. This broadcast makes the capital market sure that firm provides informationimpartially.This study tries to examine the relation between the predicted earning by managementand the firm value and risk. Sampling is done by systematic elimination method andregression analysis was used for testing hypothesis. Sample consists of 178 firms whichare listed in Tehran Stock Exchange and their data were statistically analyzed during theyears of 2007 to 2011; therefore, the sample size in this study is 1068. The results oflogistic regression has shown that the firm reported prediction of earning per share ispotentially considered by capital market , and the activists in this market would use thesefigures to decide in providence model for investing. Manuscript profile -
Open Access Article
52 - The Impact of Earning Quality on Excess Returns with Regard to Momentum the Impact of Earning Quality on Excess Returns with Regard to Momentum Category 24's portfolio technique for seasonal
vahid bekhradi nasab Fatemeh JolanejadTehran Stock Exchange has not lived and somewhat inefficient. Mechanisms and rules governing this market is still not implemented in such a way that the quality of data and information provided by member companies to deliver optimal.and suffered not because of pricing e MoreTehran Stock Exchange has not lived and somewhat inefficient. Mechanisms and rules governing this market is still not implemented in such a way that the quality of data and information provided by member companies to deliver optimal.and suffered not because of pricing errors. Probably the most attention of users of financial statements, the income statement is focused on the lowest row. In the eyes of most, profit accounting tool for making logical decisions. The hypothesis of this study are as follows: First hypothesis: Earnings Persistence on the absolute value of the excess return a negative influence. The second hypothesis: Earnings Predictability on the absolute value of the excess return a negative influence. Hypothesis: smoothing on the absolute value of the excess return a negative influence. The fourth hypothesis: quality accruals on the absolute value of the excess return a negative influence. Finally, considering conditions and above limitations, among all companies accepted in Tehran Stock Exchange, 86 companies were selected during 2005 to 2015. Also, to analyze data and estimate research models, ordinary squares regression model of panel data in common effects method, permanent effects or random effects are used. In this regard, to analyze data and calculate research variables, excel software 2010, and perform statistical tests, and for final analyses, views software, version 7, were applied. In general indicates that measures the quality of earnings on excess stock returns based on Fama and French three-factor model, taking into account the trend of stock prices of listed companies on Tehran Stock Exchange, is impressive. In this study of four indicators to measure earnings quality, earnings stability, predictability of earnings, accruals quality and smoothing was used as the four hypothesis that the effect of these measures on additional efficiency gains from the difference between the real Return expected return achieved was measured and the results of the test showed that the hypothesis were accepted theories, the literature cited in the literature and theoretical framework also matched Manuscript profile -
Open Access Article
53 - Assessing the moderating role of corporate governance system on the relationship between investors' emotional tendencies and changes in stock returns of companies listed on the Tehran Stock Exchange
Elham Farokhi Saeid JabbarzadehSome studies have shown that investors' emotions can influence their financial and investment decisions, as well as stock returns; On the other hand, stock risk can also affect this relationship; Therefore, the present study has examined the moderating role of corporate MoreSome studies have shown that investors' emotions can influence their financial and investment decisions, as well as stock returns; On the other hand, stock risk can also affect this relationship; Therefore, the present study has examined the moderating role of corporate governance system on the relationship between investors' emotional tendencies and changes in stock returns of companies listed on the Tehran Stock Exchange.In this study, the independent variable is investors 'feelings and the dependent variable is stock return fluctuations. To test the research hypotheses, the research model estimation method in the form of panel data and analysis based on the model of fixed effects and random effects by Eviews software based on composite data has been used. The sample includes 139 companies listed on the Tehran Stock Exchange in the period 1394-1399, which have been selected by a systematic elimination method. Findings showed that there is a significant relationship between investors' emotional tendencies and fluctuations in stock returns. Also showed that the variable of institutional shareholders can moderate the relationship between investors' emotional tendencies and fluctuations in returns. Manuscript profile -
Open Access Article
54 - پیش بینی نرخ ارز در بازار سرمایه با استفاده از مدل های میانگین متحرک خود رگرسیون انباشته و شبکه عصبی )مطالعه موردی: دلار استرالیا، دلار کانادا، ین ژاپن و پوند انگلستان(
Mohammad Ehsanifar Reza Ehtesham RasiMonetary policy in order to prevent losses arising from changes in exchange rates of disruptive are Always trying to find a suitable method to predict exchange rates. However, multi-dimensional characteristics of the converter makes it is complicated and nonlinear behav MoreMonetary policy in order to prevent losses arising from changes in exchange rates of disruptive are Always trying to find a suitable method to predict exchange rates. However, multi-dimensional characteristics of the converter makes it is complicated and nonlinear behavior. One of the traditional methods of forecasting, time series analysis, which is based on two as sumptions static linearity. Some doubts about the performance of these traditional models have been created One of the alternative methods, artificial neural networks that In some cases are shown a good potential for time series prediction. In this Article , After reviewing the research conducted to clarify the predictive ability of mass moving average models and Artificial Neural Networks to compare The two methods for the prediction of the daily exchange rate has been made in the period from 01.01.1990 till 01.01.2012. The results showed that the neural network approach estimates the Autoregressive Integrated Moving Average (ARIMA) method provides better responses. In this study, MATLAB software and computational tools and data STATGRAPHICS economies of Australia, Canada, Japan and the United Kingdom, and the dollar exchange rate in those countries than in America is using. Manuscript profile -
Open Access Article
55 - Using neural network approach to predict company’s profitability and comparison with decision tree c5 and support vector machine (svm)
Malihe Habibzade Mostafa EzadpourProfit as one of the most important indicators of measuring the performance of the economic unit is one of the important accounting issues that has a high status due to the competitive environment and the importance of quick and proper decision making by managers. There MoreProfit as one of the most important indicators of measuring the performance of the economic unit is one of the important accounting issues that has a high status due to the competitive environment and the importance of quick and proper decision making by managers. Therefore, it is important to analyze the index, factors affecting it and predict profitability. In this regard, the present study was conducted by selecting a sample of 124 observations for the period from 1387 to 1395, based on the basic information of the companies financial statements; the effect of 34 variables on the accuracy of predicting the profitability of the accepted companies by Tehran stock exchange, has been investigated. Tree C5 method was used to determine the significant variables in predicting profitability due to the high ease of understanding of the model. Finally, after determining the effective variables and identifying 8 variables, the accuracy of the predictions was measured using the neural network technique, the C5 decision tree and the backup vector machine (SVM), and the results from these three algorithms were compared. The results of the comparison show that using the c5 decision tree and the 8 variables have the best prediction with accuracy of 93.54%, and then the neural network model is 81.45% more accurate than the supported vector machine (69.35%) and has an error. Manuscript profile -
Open Access Article
56 - Predict the trend of stock prices using XCS based on genetic algorithms and reinforcement learning
Ahmad Reza PakraeiDevelopments for investigation in the area of artificial intelligence and machine learning, especially in the field of evolutionary computation not only enabled us for having more effective analysis of data, but also providing the ability to use it for under MoreDevelopments for investigation in the area of artificial intelligence and machine learning, especially in the field of evolutionary computation not only enabled us for having more effective analysis of data, but also providing the ability to use it for understanding any underlying model of financial markets. Economists, statisticians, and finance teachers were always interested in the development and experiment of stock price behavioral models. XCS is a compound system of genetic algorithm and reinforcement learning, which has on-line interaction with the environment and the ability of learning from its own experience. In this study we will provide a model which predicts the movements of next day‘s stock price on one of the corporations in Tehran stock exchange based on historical data and different technical indicators by using XCS. Then, efficiency of the proposed model was measured in comparison with the random walk model. Results showed that the proposed model has more predicting accuracy in comparison with that random walk model Manuscript profile -
Open Access Article
57 - Analyzing risky and no risky approach of investment opportunities levels on share return prediction ability
Leila Shirnejhad sina kheradyar ebrahim chiraniThe goal of this study is analyzing investors’ decision based on different levels of investment opportunities based on risky and no risky approach on share return prediction ability. In this study, concentration is on using three regression models with replacement MoreThe goal of this study is analyzing investors’ decision based on different levels of investment opportunities based on risky and no risky approach on share return prediction ability. In this study, concentration is on using three regression models with replacement ability on variable coefficient of investment opportunities levels that can analyze share return prediction ability from viewpoint of risky and no risky investors. Study sample includes 113 firms from accepted companies in Tehran stock exchange that includes a time period of ten years from the beginning of 2008 to the end of 2017. Results show that only when investment opportunities level is average, share return prediction ability based on risky approach exists, and against, when investment opportunities level is high and low, share return prediction ability is performed based on investment no risky return. Thus, investment opportunities level has important roles on basis of no risky approach on share return prediction ability. Manuscript profile -
Open Access Article
58 - Investigation of Volatility Forecast Errors using Geometric Brownian Motion and GARCH Models in Sector Indices of Tehran Securities Exchange
Ershad Emami Alireza Heidarzadeh HanzaeiCurrent study compares forecasting capability of GARCH (1,1) against Geometric Brownian Motion, GBM, model for daily volatility of indices. The question is to study whether accuracy of GBM forecast differ significantly from its comparing model. Our data consists of 5.5 MoreCurrent study compares forecasting capability of GARCH (1,1) against Geometric Brownian Motion, GBM, model for daily volatility of indices. The question is to study whether accuracy of GBM forecast differ significantly from its comparing model. Our data consists of 5.5 years (2015 – 2019) of daily logarithmic returns from 38 sector indices within Tehran Stock Exchange. The data was split into estimation period (5 years of daily data) and forecast period (daily data of the remaining 6 months). The competing models were estimated using maximum likelihood method and based on moving window approach, in which the length of estimating period was kept fixed, and projections were conducted on a daily basis. Root Mean Square Error, RMSE, approach was employed to measure forecasting error of each model. The one with less error will express more capability in forecasting daily volatility. With only three instances of a precise forecast, GARCH showed a relatively worse performance, in comparison to GBM.. Manuscript profile -
Open Access Article
59 - Identifying Banking Crisis Using Banking Stress Index in Iranian Economy (Dynamic Factor Model)
samineh ghasemifar Abolfazl Shahabadi shamsollah shirinbakhsh mirhosien mousavi azam ahmadianBy the fact that most of the public and private sector financing comes from the country's banking sector, It is important to maintain stability and prevent a crisis in the banking system. The purpose of this study is to identify the banking crisis using the Banking Stre MoreBy the fact that most of the public and private sector financing comes from the country's banking sector, It is important to maintain stability and prevent a crisis in the banking system. The purpose of this study is to identify the banking crisis using the Banking Stress Index in the Iranian economy for the period of 1398-1388. The Banking Stress Index is the best benchmark for assessing the banking crisis that reflects uncertainty, instability and financial friction in the banking system. In this study, the design of a bank stress index was performed using a dynamic factor model. This model is estimated by the maximum likelihood method and the stochastic pattern of missing data. Using six variables determining the banking crisis in the country, two banking stress indices with two different natures have been estimated in time series to examine the stability of the banking system. Finally, both indices of stress showed estimation; there is a precise timing of the coincidence between the greatest amounts of bank stress and the shocks to the Iranian economy. It was also concluded that bank stress indicators reflect the effects of external factors, including sanctions on the banking system fundamental weaknesses of the banking system, as well as being able to predict banking crises Manuscript profile -
Open Access Article
60 - An investigate the effect managerial optimism on investment sensitivity to cash flow
Allahkaram Salehi Rohallah Mosavei Mohammad MoradiThe sensitivity of investment to cash flow is one of the issues that have recently been the focus of financial researchers. This measure through the changes in company capital expenditures to per unit change in cash flow, measurement is made. The aim of this study was t MoreThe sensitivity of investment to cash flow is one of the issues that have recently been the focus of financial researchers. This measure through the changes in company capital expenditures to per unit change in cash flow, measurement is made. The aim of this study was to evaluate managerial optimism measure and its impact on the sensitivity of investment to cash flow with regard to the presence or absence of financial constraints on listed firms in the Tehran Stock Exchange. Thus, financial information of 100 listed firms in Tehran stock exchange investigates during 2007 to 2013. The number of data collected for this study was 700 years–company. In order to test hypotheses, multiple regression with the panel data approach, and software’s SPSS21 and Eviews7 has been used. Our results’ study shows a positive and significant relationship between managerial optimism and investment cash flow sensitivity both for the full sample, and also between firms classified to firms with financial constraints and without financial constraints. Also findings indicate that the Investment cash flow sensitivity under managerial optimism stronger for constrained firms than unconstrained firms Manuscript profile -
Open Access Article
61 - The Influence of socio-cultural factors by role of mediator Trust on participation in the stock (Case Study: Iran Stock Market)
M. Ali Motafaker Azad Hosein Asgharpour S. Abbas Mousavian Reza Ranjpour Mohsen Amini KhouzaniThis study aimed to investigate the influence of socio-cultural factors structure of participation in the stock, according to Securities and Exchange mediator of trust in Iran.The sample group consisted of 398 samples were selected based on random sampling. For statisti MoreThis study aimed to investigate the influence of socio-cultural factors structure of participation in the stock, according to Securities and Exchange mediator of trust in Iran.The sample group consisted of 398 samples were selected based on random sampling. For statistical analysis of the correlation coefficient method, hierarchical regression and structural equation modeling (SEM) was used. The results show that although the test variables, socio-cultural factors influence of some variables such as beliefs, participation in stock or reject, such as education, income, and legislation is approved, but by examining the variables of trust, such as optimism, ambiguity aversion and risk aversion and direct and significant impact of these variables on participation in the exchange on the role of influential variables related to socio-cultural factors is stressed. The results of multiple regression analysis correlation and model the role of trust in the relationship between socio-cultural factors contribute to the exchange as a mediator confirmed. In the following through compliance data and conceptual model, structural equation modeling to assess the impact of trust as a mediator was fitted and the Influence of socio-cultural factors by role of mediator Trust on participation in the stock confirmed Manuscript profile -
Open Access Article
62 - Comparison of various static and dynamic artificial neural networks models in predicting stock prices
علی اکبر نیکواقبال نادیا گندلی علیخانی اسماعیل نادریAbstractIn this disquisition, has been paid to comparing the performance of static anddynamics neural network by purpose choosing appropriate model in predicting of TehranStock Exchange. The data used in this study consists of daily and interval of time1388/1/5 to 1390/ MoreAbstractIn this disquisition, has been paid to comparing the performance of static anddynamics neural network by purpose choosing appropriate model in predicting of TehranStock Exchange. The data used in this study consists of daily and interval of time1388/1/5 to 1390/8/30, that Including 616 observation for in sample and out of sampleforecasting. Approximately 90% of these observations (556 data) use to estimatecoefficients of the model and the rest of them (60 data) use to forecast out of sample.Models are also employed in this research; two stationary neural network models such asfuzzy neural network (ANFIS) and artificial neural network (ANN) and a dynamicregression neural network model (NNARX). The results of this survey indicate thatAccording to Criteria to calculate the forecast error, among Mean squared error (MSE)and root mean square error (RMSE), Fuzzy neural network model of static, dynamicregression models, neural networks, and finally static artificial neural network modelshave lowest prediction error, Respectively. Manuscript profile -
Open Access Article
63 - Study of Moving Averages Indicators Efficiency in Technical Analysis for Forecasting Stock Price in Selected Top Companies Tehran Stock Exchange
سید علی نبوی چاشمی آیت الله حسن زادهThe aim of the study is to answer the following question: which of the predictive indicators used in this study is the best way for predicting stock price, and is considered as the higher credibility for predicting stock price in the Tehran stock exchange? For this reas MoreThe aim of the study is to answer the following question: which of the predictive indicators used in this study is the best way for predicting stock price, and is considered as the higher credibility for predicting stock price in the Tehran stock exchange? For this reason it is used the methods of a simple moving average and Weighted moving average and exponential moving average for symbol periods of 30 days, 60 days and 90 days. And then predicted results are compared with the actual price, and finally, various methods have been evaluated by two different indexes consist of Mean Absolute Deviation (MAD) and Tracer Symbol (TS).The results show that the exponential moving average methods for thirty-days period is entitled the highest credibility for predicting stock price Manuscript profile -
Open Access Article
64 - Forecasting Petroleum Futures Markets Volatility with GARCH and Markov Regime-Switching GARCH Models
مرتضی بکی حسکوئی فاطمه خواجوندIn this paper we compare a set of different standard GARCH models with a group ofMarkov Regime-Switching GARCH (MRS-GARCH) in terms of their ability to forecastthe petroleum futures markets volatility at horizons that range from one day to onemonth. To take into account MoreIn this paper we compare a set of different standard GARCH models with a group ofMarkov Regime-Switching GARCH (MRS-GARCH) in terms of their ability to forecastthe petroleum futures markets volatility at horizons that range from one day to onemonth. To take into account the excessive persistence usually found in GARCH modelsthat implies too smooth and too high volatility forecasts, MRS-GARCH models, wherethe parameters are allowed to switch between a low and a high volatility regime, areanalyzed. Both gaussian and fat-tailed conditional distributions for the residuals areassumed, and the degrees of freedom can also be state-dependent to capture possibletime-varying kurtosis. The forecasting performances of the competing models areevaluated with statistical loss functions. Under statistical losses, we use both tests ofequal predictive ability of the Diebold-Mariano-type and test of superior predictiveability, such as Whites Reality Check and Hansens SPA test. The empirical analysisdemonstrates that MRS-GARCH models do really outperform all standard GARCHmodels in forecasting volatility at shorter horizons according to a broad set of statisticalloss functions. At longer horizons standard asymmetric GARCH models fare the best.All this tests reject the presence of a better model than the MRS-GARCH-t in thisresearch Manuscript profile -
Open Access Article
65 - Long memory investigation and application of wavelet decomposition to improve the performance of stock market volatility forecasting
شمس اله شیرین بخش اسماعیل نادری نادیا گندلی علیخانیBecause of very large frequency and volatility in Financial markets Indicators, acertain type of non stationary is created that it refers to the fraction non stationary. Thiscauses, provides Long memory in this type of time series. Hence, this study has inaddition to ex MoreBecause of very large frequency and volatility in Financial markets Indicators, acertain type of non stationary is created that it refers to the fraction non stationary. Thiscauses, provides Long memory in this type of time series. Hence, this study has inaddition to examine the existence of the long memory in both mean and varianceequations in the return series of Tehran stock exchange, Pays to forecasting the volatilityof this index. For this purpose, the daily data from fifth Farvardin 1388 to eighteenthOrdibehesht 1391 is used. Our results confirm the existence of Long Memory in bothmean and variance equations. However, among others, based on the information criteriaand MSE, ARFIMA (1,2)-FIGARCH(BBM) model has been selected as the bestspecification to model and forecast the volatility of Tehran stock exchange’s return. Aswell, in order to Forecasting the volatility of this series, was used Combination of theabove model with Level and decomposed data. The results show that, according to theforecasting error criteria (MSE and RMSE), the result of model’s based on decomposeddata (with wavelet technique), more acceptable. Manuscript profile -
Open Access Article
66 - Dynamic Analysis of Uncertainty Transmission Pattern in Financial, Housing and Macroeconomic Sectors
hamidreza hamidi mirfeiz fallah shams hossein jahangirnia mojgan safaThe main goal of the current study is to investigate the contagion of uncertainty between sectors (finance, housing and macroeconomics) using a dynamic approach. In this regard, using monthly data in the period from 2008:4 to 2020:3, DCC-GARCH models and generalized for MoreThe main goal of the current study is to investigate the contagion of uncertainty between sectors (finance, housing and macroeconomics) using a dynamic approach. In this regard, using monthly data in the period from 2008:4 to 2020:3, DCC-GARCH models and generalized forecast error variance decomposition (GFEVD), The overall dynamic relationship as well as the directional pairs dynamic relationship of uncertainty indicators between the mentioned sections are investigated. The results of this study show that the housing sector, with the exception of the beginning of 2017, is a net receiver of uncertainty from the other two sectors. Also, the results of the current research show the dual role of the financial sector in the mechanism of inter-sector uncertainty transfer, so that at some periods it is a net receiver of uncertainty and at some other periods (including the years 2017 and 2018) it is a net source and transmitter of uncertainty in the three indicators system. Inflation uncertainty, as an index of macroeconomic uncertainty, is a major source of uncertainty and a transmitter of uncertainty to the financial and housing sectors. Manuscript profile -
Open Access Article
67 - Capability Comparison of the Models based on Long Memory and Dynamic Neural Network Models in Forecasting the Stock Return Index in Tehran Stock Exchange
اکبر کمیجانی اسماعیل نادریThe aim of this study is to introduce an efficient nonlinear model for predicting thereturn of Tehran Stock Exchange (TSE) Price index. For this purpose, the daily timeseries of price index from Farvardin 1388 to Aban 1390 is used. This study includes616 observations; 9 MoreThe aim of this study is to introduce an efficient nonlinear model for predicting thereturn of Tehran Stock Exchange (TSE) Price index. For this purpose, the daily timeseries of price index from Farvardin 1388 to Aban 1390 is used. This study includes616 observations; 90% of which used for estimating coefficients and the remaining 60observation are deduced for out of sample forecasting. By comparing the results of anonlinear dynamic artificial neural network (NNAR) and a nonlinear regression model(autoregressive fractional integration moving average «ARFIMA»), we found thatNNAR models have better performance in out of sample forecasting based on meansquare error criteria (MSE) and root mean square error criteria (RMSE) than thenonlinear regression models (ARFIMA). Manuscript profile -
Open Access Article
68 - The Predication of Stock Price Using Firely Algorithm
Ali Bayat Zeynab BagheriIn this study, the prediction of stock price of some manufactors listed in Tehran stock market and some others, using firefly algorithm has be done.In this study firstly, we used 16 variables for a period of 3 years (1388-1392) to educating the algorithm and after that MoreIn this study, the prediction of stock price of some manufactors listed in Tehran stock market and some others, using firefly algorithm has be done.In this study firstly, we used 16 variables for a period of 3 years (1388-1392) to educating the algorithm and after that , we used educated algorithm to predict the stock price of manufactors with 12 variables. the relative fault was calculated for stock prices for before and after prediction. the average of This fault isless than %6 and the result is that the stock price prediction using fire fly algorithm is achievable and possible. Manuscript profile -
Open Access Article
69 - The Proposed Model For Prediction Of GDP Using With ARIMA, Neural Networks And Wavelet Transform
bita Shaygani Amir behdad Salami Ramin KhochianiForecasting GDP, is one of the most important economic issues and due to its practical applications has attracted a lot of attentions. Methods of time series analysis and nonlinear methods such as neural network models as long as are used to forecast such variables . GD MoreForecasting GDP, is one of the most important economic issues and due to its practical applications has attracted a lot of attentions. Methods of time series analysis and nonlinear methods such as neural network models as long as are used to forecast such variables . GDP's time series is variable that after the decomposition, with wavelet - a powerful tool for processing data- and analyzing the hidden layers, at some levels, has linear behavior and at other levels, has nonlinear behavior.Therefore, the proposed method would be thus that the time series of quarterly GDP for the period 1367 to 1389 using wavelet techniques are decomposed into different scale components. Next, the approximation level (trend) and cycles with linear behavior have predicted with ARIMA model, and cycles with the nonlinear behavior have predicted with neural network model.The results show that the performance of the proposed method is better than the neural network (NARNET) and ARIMA models. Manuscript profile -
Open Access Article
70 - پیش بینی قیمت بیت کوین با استفاده از الگوریتم های یادگیری ماشین
میثم بشیری سیدحسین پاریاب -
Open Access Article
71 - The estimation of exchange rate of (IRR-Dollars) based on Purchasing Power Parity and Monetary Approach
مهدی تقوی مهدیه مرادیThis research is an estimation of the exchange rate between the US Dollar and the Iranian Rial, for the period between 1352 and 1387. Using ARDL method for hypothesis testing, and selecting the optimal model, the Mean Square Error (MSE) and Root Mean Square Error (RMSE) MoreThis research is an estimation of the exchange rate between the US Dollar and the Iranian Rial, for the period between 1352 and 1387. Using ARDL method for hypothesis testing, and selecting the optimal model, the Mean Square Error (MSE) and Root Mean Square Error (RMSE) are used to test our hypothesis. The selection of the optimal model for prediction is based on the Purchasing Power Parity (PPP) theory and the Monetary Approach to Balance of Payment. The results of this study indicate that the PPP model is a more accurate indicator of the exchange rate, and is therefore preferred to the monetary approach. Manuscript profile -
Open Access Article
72 - Proposing a synthetic approach (FARIMA) by employing ARIMA and fuzzy regression methods in order to forecast crude oil price
قدرت الله امام وردی مریم شهابی طبریThe ARIMA model is a precise forecasting model for short time periods, but the limitation of a large amount of historical data is required. However, in our society, due to uncertainty and rapid development of new technology, we usually have to forecast future situations MoreThe ARIMA model is a precise forecasting model for short time periods, but the limitation of a large amount of historical data is required. However, in our society, due to uncertainty and rapid development of new technology, we usually have to forecast future situations using little data in a short span of time. The historical data must be less than what the ARIMA model employs which limits its application. The fuzzy regression is able to forecast model which is suitable for the uncertain condition and with little attainable historical data. But the results of this model cannot be encouraging because the spread is wide in some cases. The researchers do try to combine the advantages of the fuzzy regression and ARIMA models to formulate the FARIMA model and to overcome the limitations of the fuzzy regression and ARIMA model. Therefore, in this study, a synthetic fuzzy auto regressive integrated moving average (FARIMA) is employed to forecast crude oil price. The findings show that the proposed method can get more satisfactory results. Manuscript profile -
Open Access Article
73 - پیشبینی بازدهی شاخص صنعت پتروشیمی در بورس اوراق بهادار تهران با استفاده از مدلهای ARIMA و ARFIMA
محسن اشراقی فرهاد غفاری تیمور محمدی -
Open Access Article
74 - Anticipation of Iran Mercantile Exchange (IME) gold coin price using Artificial Neural Network Approach with GMDH Algorithm
عباس معمار نژاد وحید فرمان آراThe economy of every country is composed of different sectors in which, the relationship amongst them determines the dimensions of the economy of that country. The capital market together with money market make up the financial market as the main arteries of an economy. MoreThe economy of every country is composed of different sectors in which, the relationship amongst them determines the dimensions of the economy of that country. The capital market together with money market make up the financial market as the main arteries of an economy. Their operation has a significant influence on the growth and development of the economy. In cases where there is no constructive relationship between the financial market and economic sectors, economic performance might be subject to distortions. The stock market as a fundamental pillar of the financial market plays a crucial role in facilitating investments in the capital market. Given the importance of expectations in different economic fields, the main purpose of this study, as its title explains, is to anticipate of Iran Mercantile Exchange (IME) gold coin price Therefore, after a brief review of dominant economic theories, a new method, artificial neural network GMDH, is used to forecast the impact of macroeconomic variables( including the rate u.s. dollar as foreign exchange, the price of gold coin, the price of gold and oil in termes of dollar, the over-all index of stocks, the delivery date of gold coin) on the gold coin price. The GMDH Algorithm is a nonlinear model to anticipate complex systematic relationships between variables of the model. The special feature of this deductive algorithm is recognition and screening of the most effective variables to estimate the model with training samples and omit the non-significant ones from the simulation process with testing samples. So, an attempt is made to solve the model via iterative methods to minimize the typical standard Error like RMSE, MAPE, and so on. Manuscript profile -
Open Access Article
75 - پیشبینی نرخ رشد قیمت سکه طلا در ایران با استفاده از الگوی رگرسیون دادهها با تواتر متفاوت (میداس)
عماد کاظم زاده تقی ابراهیمی سالاری مهدی بهنامه -
Open Access Article
76 - تخمین جریان نقدی شرکتهای پذیرفته شده در بورس اوراق بهادار تهران
فریدون الیاسی کماری زهرا امیرحسینی بتول زارعی -
Open Access Article
77 - The Prediction of Iran's Per Capita Health Expenditures up to 2041 Horizon Using the Genetic and Particle Swarm Optimization Algorithms
abolghasem golkhandan Somayeh SahraeiIntroduction: prediction the per capita health expenditures can be useful and effective in determining the best policies for financing and managing of health expenditures. Accordingly, the main objective of this study was to predict the per capita health expenditures tr MoreIntroduction: prediction the per capita health expenditures can be useful and effective in determining the best policies for financing and managing of health expenditures. Accordingly, the main objective of this study was to predict the per capita health expenditures trend in Iran. Methods: In this paper, we specified a health expenditure model relying on theoretical basics in order to obtain desirable forecasts. On the basis of three forms of linear, exponential and quadratic equations and using theoretical foundations in the field of per capita health expenditure function, we used genetic algorithm (GA) and particle swarm optimization (PSO) algorithm to simulate Iranians per capita health expenditure during 1979-2015. Then we selected the superior model in terms of prediction power criteria and forecast per capita health expenditure until 2041. Also, the statistical analyzes were performed using the MATLAB software version R2016b. Results: The predicted results indicate that per capita health expenditures in Iran will increase with a positive slope by 2041. The amount of this expenditure will be from $ 1081 (based on 2011 constant prices) in 2015 to $ 2628 in 2041 (about 2.5 times). Conclusion: With regard to the projected amount of per capita health expenditures up to 2041 horizon, policy makers in the health sector should take the necessary measures to finance the expenditures of this sector. Manuscript profile -
Open Access Article
78 - Comparison of Models in Predicting Cumulative Cases of Hospitalization and Death of Covid-19 (Case Study: Bahabad city
mohammad hossein karimizarchi Davood ShisheboriIntroduction: Coronavirus disease 2019 is a respiratory disease caused by acute respiratory syndrome coronavirus-2. Forecasting the number of new cases and deaths during todays can be a useful step in predicting the costs and facilities needed in the future. This study MoreIntroduction: Coronavirus disease 2019 is a respiratory disease caused by acute respiratory syndrome coronavirus-2. Forecasting the number of new cases and deaths during todays can be a useful step in predicting the costs and facilities needed in the future. This study aims to modeling, comparing the performance of models, and predict new cases and deaths efficiently in the future. Methods: In this article nine popular forecasting techniques are tested on the data of Covid-19 in Bahabad city as a case study. Using the evaluation criteria of mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and the mean absolute percentage of error (MAPE) of the models are compared. Results: The results of the analysis showed that the best model according to the evaluation criteria for forecasting cumulative cases of hospitalization of Covid-19 is the cubic spline smoothing model, and cumulative cases of death, KNN regression model. Also, autoregressive neural network and theta models for hospitalization cases, and for death cases, autoregressive neural network model has the worst performance among other models. Conclusion: This study can provide a proper understanding of the spread of covid-19 disease in this region so that by taking precautionary measures and formulating appropriate policies, this epidemic can be effectively overcome. Also, unlike other studies, this study uses 9 different techniques and their comparison, which in turn increases the confidence factor in decision making. Also, an important point is that the data should be updated in real time. Manuscript profile -
Open Access Article
79 - Investigating the Effect of Marketing Research on Marketing Proximity Through the Use of Intermediary Variables: The Relationship between the Company and Customers and the Sales Staff
homa doroudi sanaz moradiThe difference between marketing and sales is more than their semantic difference. Sales focus on the needs of the seller, marketing to the needs of the buyer. Sales are planned to turn a seller into cash, marketing aims to meet customer needs by product, including all MoreThe difference between marketing and sales is more than their semantic difference. Sales focus on the needs of the seller, marketing to the needs of the buyer. Sales are planned to turn a seller into cash, marketing aims to meet customer needs by product, including all stages of creation, delivery, and eventual consumption. The definition of business from an important customer perspective should be more relevant to the customer's perspective than the manufacturer or service provider. Production and product, regardless of customers' perspective, lead to near-nose and fall. The aim of the research is to investigate whether there is a relationship between market surveillance and market research, and this relationship has been measured with several main variables, such as customer relationship and consultation with sales staff, and the impact of variables such as gender, work experience and experience. The purpose of the study is application and in terms of collecting data, descriptive-survey. In this research, 26 managers in various industries and services were asked by random sampling method. Data analysis was done by statistical method and the results showed that managers have severe myopia. Manuscript profile -
Open Access Article
80 - Investigating Effective Factors on Purchase Intention of Luxury Products
B. Kheiri M. FathaliMarketing managers are interested in consumer purchase intentions so as to prognosticate sales of existing and/or new products and services. Purchase intentions data can help managers in their marketing decisions related to product demand (new and existing pro MoreMarketing managers are interested in consumer purchase intentions so as to prognosticate sales of existing and/or new products and services. Purchase intentions data can help managers in their marketing decisions related to product demand (new and existing products), market segmentation and promotional strategies. Luxury brand products and the motivation to buy luxury brands are becoming increasingly relevant to consumers in Asia. Luxury-purchase motivation predominantly based on Western thoughts and markets .Cultural values have been shown to influence consumer behavior in many studies. Establishing whether relationships exist between cultural values and motivation for consuming luxury products would be advantageous for the marketers of luxury products . The present study focuses on factors affecting the purchase intention of luxury products. Primary Tools for Data Collection was Likert's 5-scale questionnaire. Statistical Population is composed of all customers attending selected fancy and luxurious restaurants in Tehran. Since the statistical sample is infinite (over 100000 subjects), the sample size was determined to include 385 subjects by means of Kergesi Morgan's Table (1970), and simple random sampling method was applied. In order to analyze the data, descriptive and inferential statistics and the structural equation modeling were employed with SPSS and Lisrel software programs. The research, in terms of purpose, is practical and the method of data collection is survey. Research results suggest that the variables of consumer attitude toward luxurious products, quality of the service provided by fancy and luxurious restaurants, perception of brand and social effect affect the purchase intention, while the variables of store image (restaurant) and vanity bring about no impact on the purchase intention. In addition, the variable of vanity does not exert any moderating effect on the relation between perception of luxurious brand and purchase intention and between the social effect and purchase intention. Manuscript profile -
Open Access Article
81 - A comparative study in the theory of imprevision after the amendments of French Civil Code in 2016 and comparision with the similar jurisprudence rules in Imamiah jurisprudence
Abdolrazzagh Musanataj Seyyed Hossein Safaei Asghar Arabian Najadali Almasi Mohsen MohebiA comparative study in the theory of imprevision after the amendments of French Civil Code in 2016 and comparision with the similar jurisprudence rules in Imamiah jurisprudenceAbstractAlthough in jurisprudence the reference to the theory of Imprevision is relatively lim MoreA comparative study in the theory of imprevision after the amendments of French Civil Code in 2016 and comparision with the similar jurisprudence rules in Imamiah jurisprudenceAbstractAlthough in jurisprudence the reference to the theory of Imprevision is relatively limited, but nevertheless some rules and principles of jurisprudence such as the rule of hardship, new swindling and harmlessness in justifying such theories have been cited by legal writers. Although some jurists have equated the harmlessness, hardship and new swindling rules with the theory of Imprevision in French law, a distinction must be made between the above rules and the theory of Imprevision. However, the theory of hardship has enough consistency to resolve the troublesome situation of unpredictability and prevention until the ambiguity is resolved and a new rule is enacted. In other words, judicial modification or revocation of the contract, like the theory of non-contingency after the amendments to the French Civil Code, can be deduced from the rule of hardship.Key Word: theory of Imprevision, harmlessness rule, hardship rule, the theory new swindling Manuscript profile -
Open Access Article
82 - Accounting flexibility and managers' optimism: Test of management discretion theory
Soghra Barari Nokashti Bahman Banimahd Ahmad YaghoubnejadThe purpose of this study was to investigate the relationship between accounting flexibility and the managers' optimism in earnings forecast based on the theory of managerial discretion. The statistical sample of the research includes 129 companies from listed companies MoreThe purpose of this study was to investigate the relationship between accounting flexibility and the managers' optimism in earnings forecast based on the theory of managerial discretion. The statistical sample of the research includes 129 companies from listed companies in Tehran Stock Exchange between 2008 to 2016. The results of the research show that there is a direct and meaningful relationship between the amount of accounting flexibility with earnings predictive growth and predictive error by management. As firms with high accounting flexibility have a more optimistic prediction than companies with low accounting flexibility. Also, companies with higher accounting flexibility through earnings manipulation have been able to increase earnings above Forecast earnings and their earnings forecast error is positive, but firms with low accounting flexibility due to the effect Cumulative of the past accruals management has been confronted with a limitation on Manipulation of current period earnings and future periods, so the predictive error of their earnings is negative. According to the results of the research, it is suggested to investors and analysts to be attentive to managers' Opportunistic optimism When they use earnings Forecast by Managers Manuscript profile -
Open Access Article
83 - The Impact of Accounting Conservatism on Earnings Management Forecasting Error
Ahmad Lotfi MEISAM HAJI POREarnings is one of the important and essential components of financial statementsthat is of particular interest to financial statements users. The information which isissued with a company and as a results earnings , is based on past events but investorsneed information MoreEarnings is one of the important and essential components of financial statementsthat is of particular interest to financial statements users. The information which isissued with a company and as a results earnings , is based on past events but investorsneed information about firm’s future. Firm’s Managements who have enoughinformation and resource, hasten the efficiency of financial market by earningsforecast . Prior researches has indicated that managements forecasts have effect onstock price, stock markets liquidity and analysts forecasts . On the other hand, theaccuracy or error of predicted earnings is affected by size, age , structure of companyand etc . Also it’s confirmed that managements psychological bias has impact ontheir forecasts . further empirical researches show that accounting policies areconservative and become more conservative from thirty past years (Watts,2003).Basu(1997) and following him found evidence of accounting conservatismdevelopment. Li(2007), also, find that in times of growth in investment, accountingconservatism leads to a downward bias in reported earnings and net assets. In thispaper, we examine the effect of accounting conservatism on management earningsforecasting error. Empirical findings are according to a sample from 88 companies ofTehran stock exchange during the period of 1998-2008 support our hypotheses. Inother words companies which have more conservative policy have less earningsforecasting error . Manuscript profile -
Open Access Article
84 - A study of the association between financial reporting frequency and management myopia
Yasser Rezaei Pitenoei Mohammad GholamrezapoorIncreased financial reporting frequency is characterized as an appropriate mechanism which contributes to the enhancement of managerial information transparency and influences investment decision-making process. Despites of these significant influences, however, some st MoreIncreased financial reporting frequency is characterized as an appropriate mechanism which contributes to the enhancement of managerial information transparency and influences investment decision-making process. Despites of these significant influences, however, some studies reveal that it can persuade CEOs to adopt myopic approaches. The present study thus seeks to investigate the relationship between financial reporting frequency and management myopia in the firms listed on the Tehran Stock Exchange over the period of 2013-2017. In pursuit of this goal, the research hypothesis is built upon a sample of 51 listed firms and then tested using multivariate logistic regression model. The results document a significantly positive relationship between financial reporting frequency and managerial myopia. In other words, increasing the frequency of financial reporting will lead to management myopia, which causes executives to ignore investment in R&D, marketing, and long-term activities that benefit the company. Manuscript profile -
Open Access Article
85 - The Association between Management Earnings Forecast Errors and Corporate Governance Structure in Tehran Bourse
سید علیرضا موسوی حمید زارعی سمیرا هنربخشIn this study, we examine the relation between management earnings forecasterrors with corporate governance structure of listed companies in Tehran Bourse. Weshould mention that corporate governance structure which are studied here are: Thepercent ownership of board mem MoreIn this study, we examine the relation between management earnings forecasterrors with corporate governance structure of listed companies in Tehran Bourse. Weshould mention that corporate governance structure which are studied here are: Thepercent ownership of board members, the number of board members, the number ofnon-executive board members and Growth opportunity.The numbers of statistic community are 363companies in Tehran Bourse whichdue to the limitation of this study we select just 146 companies from these statisticcommunities during 1383-1387. For preparation the literature and the history of thissurvey we use the information from Financial Statement, Tadbir pardaz soft ware,Bourse library and Tehran Bourse archives.For testing hypothesis we use Pearson coefficient of correlation and multi variableRegression model. The result shows that there are positive relations between thepercent ownership of board members, the number of board members and the numberof non-executive board members with accuracy of management earnings forecast,while there is a negative relation between Growth opportunities with accuracy ofmanagement earnings forecast. Testing hypotheses show that all of the surveyhypotheses are confirmed Manuscript profile -
Open Access Article
86 - The Investigation of Corporate Governance Characteristics on Management Earnings Forecast Quality in Tehran Stock Exchange
غلامحسین مهدوی سید مجتبی حسینی زهره رئیسیThe importance of earning forecast and its impact on economic decisions ofinvestors in the stock market is widely known. There are many researches about thequality of management earnings forecast to identify the factors that have effects on it.So this study examines whe MoreThe importance of earning forecast and its impact on economic decisions ofinvestors in the stock market is widely known. There are many researches about thequality of management earnings forecast to identify the factors that have effects on it.So this study examines whether corporate governance attributes have an effect on thequality of management earnings forecast. The measures of corporate governance areboard attributes, institutional shareholders and auditing committee. Managementearnings forecast quality is then measured by management earnings forecast accuracyand bias. We used data of 100 companies for the period of 1384-1388 in Tehran stockexchange. The results show that corporate governance variables in Iran have no effecton the quality of management earnings forecast. Manuscript profile -
Open Access Article
87 - Bloated Balance Sheet and Substitute Mechanisms to Avoid Negative Earnings Surprises
Hassan Farajzadeh Dehkordi Hassan Hemmati Hale SanaeeIn this paper, we examine the role of the balance sheet as a constraint on accrual-basedearnings management and its impact on the tradeoffs between accrual-based earningsmanagement, real earnings management, and forecast guidance in managing earningssurprises. Overall, MoreIn this paper, we examine the role of the balance sheet as a constraint on accrual-basedearnings management and its impact on the tradeoffs between accrual-based earningsmanagement, real earnings management, and forecast guidance in managing earningssurprises. Overall, our evidence suggests that managers turn to real earnings management or downward forecast guidance as a substitute mechanism to avoid negative earnings surprises when their ability to manipulate accruals upward is constrained by the extent to which net assets are already overstated in the balance sheet. Nevertheless, our evidence should be interpreted with caution given the limitations of our study. In particular, our study uses management’ earnings forecasts rather than analysts’ earnings forecasts. Manuscript profile -
Open Access Article
88 - The relationship between short-sighted profit quality management and investments in companies listed on the Tehran Stock Exchange
Somayyeh Talezari Mohammadreza AbdoliManagers myopic Than Their activities bias or Specific trends And this causes serious limitation And important for considering options and recommendations on the selection and decision-making. Given the importance of this issue, In this study examines the relationship b MoreManagers myopic Than Their activities bias or Specific trends And this causes serious limitation And important for considering options and recommendations on the selection and decision-making. Given the importance of this issue, In this study examines the relationship between short-sighted profit quality management and investments in companies listed on the Tehran Stock Exchange was paid. The sample includes 127 companies in Tehran Stock Exchange for the period 1389- 1393 and multivariate regression model was used econometric panel data. Results showed an increase in short-sighted management can be reduced earnings quality and corporate investment. The findings suggest that lead to short-sighted management decisions Nakaramdshdh and affects firm value. This management style has detrimental effects on firm value and investment opportunities loses. Results control variables showed a control variable Size, MV, Cash, RoA positive effect and negative effect on earnings quality and the LEV variable investment company. Manuscript profile -
Open Access Article
89 - Forecasting Fraudulent Financial Reporting Through Artificial Neural Network
Mojtaba Tarasi Bahareh Banitalebi Behzad ZamaniIn this study, the ability of artificial neural networks (ANN) as a novel method for predicting the likelihood of fraudulent financial reporting of listed companies in Tehran Stock Exchange in a period of 9 years between the years 2006 to 2015 were studied. For this pur MoreIn this study, the ability of artificial neural networks (ANN) as a novel method for predicting the likelihood of fraudulent financial reporting of listed companies in Tehran Stock Exchange in a period of 9 years between the years 2006 to 2015 were studied. For this purpose, the information contained in the financial statements and financial ratios and Multilayer Perceptron model, which includes an input layer, hidden layer of visibility software MATLAB, and an output layer is, the likelihood of distorted presentation of the financial report of fraudulent financial reporting through techniques neural network was evaluated. In this regard, the first seven years of information companies, to develop and train the neural network, data validation and verification of the eighth to the ninth year of training, networking and data as test data and test network were designed .Finally, with regard to the results, it was found that the neural network modeling techniques based on neural network integrity is 97.4% and the design and rigorous training, neural networks can be designed with reasonable accuracy the probability to detect and predict fraudulent financial reporting companies. Manuscript profile -
Open Access Article
90 - The effects of judgmental biases on managerial accounting techniques
فریدون رهنمای رودپشتی هاشم نیکومرام آرزو جلیلیThe main objective of this article is to investigate the effects and consequences ofbehavioral biases – at the judgmental level – on managerial accounting techniques. Inthis respect, the individual judgmental biases – including: Over Confidence, Optimi MoreThe main objective of this article is to investigate the effects and consequences ofbehavioral biases – at the judgmental level – on managerial accounting techniques. Inthis respect, the individual judgmental biases – including: Over Confidence, Optimism,Hindsight, and Representativeness biases, - are treated as independent variables, whilethe managerial accounting techniques functions– including: Budgeting and Forecasting,Evaluating the undesirable consequences of the risk, Performance Evaluation, TakingRisky Options, Ranking and Weighting the potentiality of the risk in different ventures,and feedback assessment of the risk potentiality, - are considered as dependentvariables.The Structural Equation Modeling Technique, with Maximum Accuracy (ML) hasbeen utilized for hypothesis test. The following results are the overall findings:1) The results showed that, there is an opposite relationship between OverConfidence and Optimism biases, on one hand, and managerial accountingtechniques on the other hand;2) A meaningful straight linkage between Hindsight bias and managerialaccounting techniques was observed;3) No potential relationship between Representativeness bias and the dependentvariable could be found; Manuscript profile -
Open Access Article
91 - Comparative between cost prediction using statistical methods and neural networks
امیر محمدزاده نسرین مهدی پور آرش محمدزادهPrediction of total cost of water helps the Isfahan municipality to optimize thewater usage in its 14 urban zone. The total cost of water, basically, depends ondifferent parameters. Generally, the analytically prediction of the total cost is verydifficult if not impossi MorePrediction of total cost of water helps the Isfahan municipality to optimize thewater usage in its 14 urban zone. The total cost of water, basically, depends ondifferent parameters. Generally, the analytically prediction of the total cost is verydifficult if not impossible. Thus, applying intelligent systems such as neural networkmodels can be a good alternative. In this paper, using multi-layer perceptron neuralnetwork and error back propagation algorithm, the total cost of municipal water in theIsfahan municipality is calculated based on parameters such as per capita populationand area of each urban zone. In this paper, a model for simulation and prediction ofthe annual total cost of water in Isfahan municipality is developed. The simulationmodel is developed using the regression and the neural network model is built usingdata from 2004 to 2009. Finally, the neural network method is selected as the mainsimulation method for forecasting the total cost of water in the 14 urban zones ofIsfahan. Manuscript profile -
Open Access Article
92 - Effect of Stock Price Pressure on Management Earnings Forecasts
Farhad Sharafi Shadi Shahverdiani Zohreh HajihaManagement earnings predictive quality, is much higher than predictions by individuals outside the organization. Because managing more information about the status of the company, it is aware of the current plans of the company and has access to the details of financial MoreManagement earnings predictive quality, is much higher than predictions by individuals outside the organization. Because managing more information about the status of the company, it is aware of the current plans of the company and has access to the details of financial information from previous periods. In addition, it often allocates significant resources to financial forecasts. The main issue is not whether stock price pressures affect the management earnings predictive quality? The main objective of this research is to investigate the effect of stock price pressure on management earnings expectations in listed companies in Tehran Stock Exchange. Measurement criterion for managers' earnings forecast; Earnings per share are forcasted, managers earnings forecast error and manager earnings aggressive forecast. To test the hypotheses of the research, multiple linear regression model has been used. The results of the survey of 140 companies listed in Tehran Stock Exchange during the period from 2011 to 2016 indicate that stock price pressures have a negative effect on managers earnings forecasting. In addition, the research evidence showed that stock price pressures have a positive effect on the forecast error of managers' earnings. Also, the results showed that stock price pressure had a positive effect on the manager earning aggressive forecast. These results indicate the importance and effectiveness of stock price pressures in managerial earnings forecasts. Manuscript profile -
Open Access Article
93 - Investigating the Effect of Information Environment on the Relationship between Management Forecast Error and Idiosyncratic Risk in Companies Accepted in Tehran Stock Exchange
Mahsa Kaffashpour yazdi Akram Taftiyan Mahmoud MoeinaddinInvestors in the stock market decide on the risk factors, returns, and stock liquidity. Considering the impact of the company's disclosure quality on these factors, management's forecast errors can increase the risk of a company. On the other hand, by strengthening the MoreInvestors in the stock market decide on the risk factors, returns, and stock liquidity. Considering the impact of the company's disclosure quality on these factors, management's forecast errors can increase the risk of a company. On the other hand, by strengthening the company's information environment, perhaps the weaknesses of the management forecast error can be reduced. So this study investigates the effect of information environment on the relationship between management forecast error and idiosyncratic risk. Study population includes qualified companies in Tehran stock exchange. After using systematic elimination methods, data from 56 companies in 2010 -2017 period is used, but for extracting data the period is 2009 to 2017. To test study hypothesis, multi-variable regression methods using panel data is utilized. Information asymmetry is used to evaluate information environment; Management error in forecasting net income, operating income and sales is used for estimating management forecast errors; and fore measuring Idiosyncratic risk, Asynchronicity and Idiosyncratic Volatility is utilized. Results of this study show a significant direct relationship between management forecast error and idiosyncratic risk. In addition, in companies with stronger information environment, the direct relationship between management forecast error and non-systematic risk is lower. Manuscript profile -
Open Access Article
94 - Providing a neural network model to predict the profits of companies listed on the Tehran Stock Exchange and comparing its accuracy with HDZ and ARIMA models
masoud asadi seyedmozaffar mirbargkar Ebrahim ChiraniProfit forecasting is an important criterion for companies and companies listed on the Tehran Stock Exchange must be very careful in forecasting their profits. This study aims to provide a neural network model to predict the profits of companies listed on the Tehran Sto MoreProfit forecasting is an important criterion for companies and companies listed on the Tehran Stock Exchange must be very careful in forecasting their profits. This study aims to provide a neural network model to predict the profits of companies listed on the Tehran Stock Exchange and compare its accuracy with ARIMA and HDZ models. The research method is an applied research in terms of purpose, an inductive research in terms of logic and a quantitative research in terms of data nature. In order to collect data, the basic financial statements of companies in the period 1398-1393 were used. In this study, neural network method was used to predict corporate profits and two models, ARIMA and HDZ, were evaluated. The results show that the rate of data convergence and regression in the first phase and in the HDZ method equal to 0.79087, in the second phase, in the ARIMA method, it is equal to 0.79184, and in the artificial neural network method, it is equal to 0.79464, which has a higher degree of convergence and regression coefficient. Based on the results, it can be seen that the designed neural network has the ability to predict stock price trends using general and industry indicators, and this, in addition to confirming the neural network's ability to predict financial areas and profitability it also confirms strategy of the price forecast on the Tehran Stock Exchange.‏ ‏‏ Manuscript profile -
Open Access Article
95 - The Effect of Earnings Management on the Relationship Between Earnings Forecast Error and Accounting Conservatism
Yaser Ahmadi Bahman Banimahd Ghodratollah Talebniya Zahra PourzamaniEarning as the most important product of the accounting information system should be of an acceptable quality. Because earning is the basis of the economic decision-making of investors. Investors tend to have information about the future, including the prediction of ear MoreEarning as the most important product of the accounting information system should be of an acceptable quality. Because earning is the basis of the economic decision-making of investors. Investors tend to have information about the future, including the prediction of earnings per share and its precautionary prediction. However, managers' opportunistic behavior by manipulating earnings reduces the reliance on information and reduces the quality of earning. In contrast to accounting conservatism, the manager's biased behavior in identifying earnings is delayed. Hence, the conservatism makes the manager and other groups, such as shareholders, receive less sums of return. This will increase the value of the company. The increased value of the company increases among all the parties in the company's division of the division and welfare of each group. Hence, this research examines the effect of earnings management on the relationship between earnings forecast error and accounting conservatism in a period of 9 years from the over a of 2009 to 2017 in 115 companies from listed companies in Tehran Stock Exchange. The results of the research show that there is a significant (positive) relation between the predictive error of earning and the accounting conservatism (as one of the criteria of the quality of earnings) in the real earnings management. But the results of this research do not confirm the significant relationship between the predictive error of earnings and accounting conservatism in accruing earnings management. Manuscript profile -
Open Access Article
96 - Managers' Risk-Taking and Optimism: Analysis of Neuro finance Model Based on Hormone Measurement
Maryam Nouraei ataallah mohammadiolgharni m iraj noravesh Kaveh Bahman PourThe aim of the current study was to investigate the role of hormones in financial behaviors. Risk-taking and optimism are two behavioral characteristics of managers and investors; for this purpose, these two behavioral factors and the level of hormones affecting them we MoreThe aim of the current study was to investigate the role of hormones in financial behaviors. Risk-taking and optimism are two behavioral characteristics of managers and investors; for this purpose, these two behavioral factors and the level of hormones affecting them were studied. The research hormones included testosterone, free testosterone, T3, T4, TSH, and cortisol, which were measured by a blood test in a medical laboratory. Age and gender were also the other two variables of the study. The statistical population included financial managers working in government institutions and banks and a standard questionnaire was used to collect qualitative data. Data analysis was performed using RSM, SPSS, and LISREL software. This experimental research is cross-sectional in terms of time, quantitative in terms of data, and fundamental-applied in terms of purpose. The results indicated that hormone levels, gender, and age have significant effects on risk and optimism. These findings are in line with the results of neurofinance research. Manuscript profile -
Open Access Article
97 - A Prediction of Urban and Rural Population by 2040
Habibollah Zanjani -
Open Access Article
98 - The presentation of energy models in programs of socio-economic development
Mohammadreza Moghaddam -
Open Access Article
99 - The impact of religious world-view of endowment on physical expanding of city (A case study of Malayer)
Majid Shams Parisa Haji Malayeri -
Open Access Article
100 - Estimating Daily Maximum Temperatures Using Artificial Networks (Case study: Kerman)
Shokoufeh Omidi ghaleh mohammadi Ahmad Mazidi Sodabh Karemi Najmeh Hassani sadi Mahboobeh Omidi ghaleh mohammadi hassan kharajporConsidering the capability of the artificial neural networks in simulating sophisticated processes, it is being used in estimation and computation of climatic parameters. The goal of this research is to estimate the daily maximum temperature in Kerman province. To this MoreConsidering the capability of the artificial neural networks in simulating sophisticated processes, it is being used in estimation and computation of climatic parameters. The goal of this research is to estimate the daily maximum temperature in Kerman province. To this aim, daily climatic parameters as input to the neural networks and daily maximum temperature as the output during a statistical period of 24 years (1989-2013) were used, the findings revealed that the output of the multi-layer perceptron neural network, considering the error amount and correlation among data, is more precise and shows lower error and more correlation in relation to the expected output (daily maximum temperature). Also, among other climatic parameters, minimum temperature and the average of the wet temperature indicated the estimation of the daily maximum temperature with lower error and more correlation in comparison to other climatic parameters. Manuscript profile -
Open Access Article
101 - Analysis of human geography role in High school books in Students spirit of social partnership case study Urmia
پریوش محمدی قشلاقمطالعه حاضر در بررسی نقش جغرافیای انسانی در کتب دوره متوسطه در روحیه مشارکت پذیری اجتماعی دانش آموزان شهرستان ارومیه انجام گردیده است. این پژوهش از نظر هدف، کاربردی و از نظر روش، تحقیقی توصیفی است و از حیث ماهیت، تحقیق همبستگی است. جامعه آماری تحقیق حاضر، کلیه دانش آموز Moreمطالعه حاضر در بررسی نقش جغرافیای انسانی در کتب دوره متوسطه در روحیه مشارکت پذیری اجتماعی دانش آموزان شهرستان ارومیه انجام گردیده است. این پژوهش از نظر هدف، کاربردی و از نظر روش، تحقیقی توصیفی است و از حیث ماهیت، تحقیق همبستگی است. جامعه آماری تحقیق حاضر، کلیه دانش آموزان شهر ارومیه مشغول تحصیل هستند می باشد. برای تحقق اهداف تحقیق حاضر سه فرضیه تدوین گردید که جهت تایید یا رد فرضیهها ازآزمون رگرسیون استفاده شد؛ نتایج بررسی حاکی ازآن است که: بنابه فرضیه اول جغرافیای انسانی در کتب دوره متوسطه بر بدبینی و بی اعتمادی دانش آموزان تاثیر معنی داری دارد. عناصر روانی بسیاری از قبیل اظهار کراهت و بیزاری اعضای خانواده از یکدیگر، بخل و حسادت و سایر حالتهای روانی مرضی وجود دارد که مانع از مشارکت پذیری بوده و از این جهت مشابه بی‏اعتمادی است؛ که جغرافیای انسانی مورد کاهش بدبینی و بی اعتمادی دانش آموزان میشود.همچنین بنا به فرضیه دوم تحقیق، جغرافیای انسانی در کتب دوره متوسطه بر نگاه جنسیتی دانش آموزان تاثیر معنی داری دارد. از آنجایی که یکی از موانع فرهنگی مشارکت پذیری تلقی جنسیت محض از نقشها و اشتغالات مربوط به جامعه است. . Manuscript profile -
Open Access Article
102 - Analysis and forecasting of precipitation in the Larestan area by Markov chain.
بهلول Alijani زین العابدین Jafarpoor حیدر GhaderiIn order to analyze the precipitation of the Larestan area, the rain days with 0.1millimeter or more were obtained from the Iranian Meteorological Organization for the1960-2003 period. First the rainy periods with different lengths were identified andtheir monthly and s MoreIn order to analyze the precipitation of the Larestan area, the rain days with 0.1millimeter or more were obtained from the Iranian Meteorological Organization for the1960-2003 period. First the rainy periods with different lengths were identified andtheir monthly and seasonal frequencies were calculated. On the monthly basis Januaryhad the highest wet days frequency and winter was the wettest but the spring was thedriest season. The wettest year had 44 rain days while only 11 days were experiencedduring the dry year. The mean daily density of rain was 8.2 mm and the mean timeinterval between successive rainy periods was 6.2 days. On the average the rainyperiod begins each year on 8 of December and ends on 6 of April.The first order Markov chain was applied to the data series to forecast the wetperiods. The model responded well and was able to forecast significantly andprecisely. The model was fitted best for the runs of one to six days proving thehypothesis of the study. Manuscript profile -
Open Access Article
103 - Evaluation Using The Lary Model is Inpredicting The employment and population Of Sanandaj City
Osman Baghadam Akbar Parheskar Masood MahdaviThe city states a space which the people has been gathered in it and provide theirlife in a permanent comparatively form upon the economic activities of area.This area can be the center of economic, commercial, educational or a combinationof them and this cause the attr MoreThe city states a space which the people has been gathered in it and provide theirlife in a permanent comparatively form upon the economic activities of area.This area can be the center of economic, commercial, educational or a combinationof them and this cause the attracting of villager people. Under standing the worth ofthe local economic activities gives move firmness to the work of programmer.Attandance of population in a civic or villager area will be actional by employmentand existence of kinds of jobs.So, there is a close relation between the levels of employment for each country,area, city or village is a so hard and also deicate work because for reaching to a exactpredicting of population in future needs using of exact methods and Models, which theLary model is in this kind of models.In this Model, economic activities has been propounded as a dish and workers ofcivic land us a paked.Sanandaj city as a center of province is in the west of Iran, and has had a prevailingrole in connection of propounding the services in a different economic and socialylevels in the area level.In one to years old section from 1335 till 1375, the population of Sanandaj city hasincreased as many as 6/8. So information of population and employment of this cityhas a high important in future. Manuscript profile -
Open Access Article
104 - Change prediction of Karoon river lengths by using historical and quantitative geomorphologic data (From Shoshtar to Arvandrod)
Jafar Morshedi Seyed Kazam Alavi panahThe study area is a part of Karoon river located in Khuzestan province in southwestof Iran. The length of this reach is about 364 km from the north of Shoshtar to theArvandrod. The changes and local difference on the river reaches consider togeological, tectonicaly, hyd MoreThe study area is a part of Karoon river located in Khuzestan province in southwestof Iran. The length of this reach is about 364 km from the north of Shoshtar to theArvandrod. The changes and local difference on the river reaches consider togeological, tectonicaly, hydrological and artificial parameter in the dry flood plain ofKhuzestan has caused some damages, risks and hazards during the time. By recognizeof fluvial environment of Karoon River and determining the changes of the river,control of these hazards is possible. Because of morphometric characteristics study ofKaroon River, for changes prediction, with use of satellite images of IRS and land satin the years of 1991 and 2007, channel length of the river has drawn, measured andanalyzed by GIS software. so total length of Karoon consider to the number of theircurves(100 curve) divided to smaller limits and crossing point selected as upper andlower limits of each curves. Then geometric parameter of channel like radius ofcurvature, mean central point of each curve, curve direction and annual rate of channelmigration measured. The results show that the most risks belong to meanderingreaches. Therefore the land use and sensitive area of river to erosion spatially oncurves if dose not controlled. There are a lot of area like farms, roads, settlement,national fields and other mankind Struthers that will be destroyed. Manuscript profile -
Open Access Article
105 - The analysis and forecasting of climatic fluctuation of khorasan
Alireza BanivahebConcerning the drought being experienced recently and its effect on planning, and economical, agricultural fields and the demands on predicting and applying different models for decision making, Markov Chains model was applied in Khorasan at Mashhad , Torbat Heydarieh , MoreConcerning the drought being experienced recently and its effect on planning, and economical, agricultural fields and the demands on predicting and applying different models for decision making, Markov Chains model was applied in Khorasan at Mashhad , Torbat Heydarieh , Birjand and Bojnord stations . This model studies the phenomena which depend on the previous ones. Here, we have studied the possibility of the occurrence of dry and wet days ( wetness threshold of 0.1 mm) , the cold days ( below ) and warm days ( above 25C) . Finally , two analyses were done using Markov Chains model. Also, for predicting 1 to 10 day periods , Xn=Pn-1 × q from statistical distribution was applied and the data was presented in the form of equiprobable maps . To analyze the provided data and maps , SPSS and SURFER softwares were applied . Manuscript profile -
Open Access Article
106 - Determining Areas Prone to Slope Movements
علیرضا Shahabfar کوروش Ehteramian محمد MotamediInvestigating slope instability and determining areas prone to slope movements bymeans of GIS has been considered by researchers in the past recent years; however,sufficient attention has not been given to the methods employed in GIS.The present article uses a cell anal MoreInvestigating slope instability and determining areas prone to slope movements bymeans of GIS has been considered by researchers in the past recent years; however,sufficient attention has not been given to the methods employed in GIS.The present article uses a cell analysis method in a slope instability studyconducted at Sanandaj Country, and has obtained an appropriate model fordetermining prone areas. While testing the model, the cell analysis method has beencapable of assessing the factors influencing slope instability and creating modificationchanges in weights and coefficients. Manuscript profile -
Open Access Article
107 - مطالعه بیماریزایی سویه ایرانی ویروس لارنگوتراکئیت عفونی در کشت سلول فیبروبلاست جنین جوجه
رؤیا صدری روزبه فلاحی شهین مسعودی سعید مهدوی سید مهراد میر سعیدی فراهانی -
Open Access Article
108 - مطالعه پاتولوژیک پنومونی بینابینی در گوسفندان کشتاری استان تهران
فرهنگ ساسانی امیر علی رئیسی مهدی مقدم -
Open Access Article
109 - Comparative evaluation of interstitial lung pattern by analog radiography and computed radiography in domestic shorthair cats
Akbarian, M., Veshkini, A.*, Masoudifard, M., Mortazavi, P. .The aim of current study was comparing the diagnostic performance of computed radiography with that of analog radiography in evaluation of interstitial lung pattern based on histopathology as a gold standard. Twenty domestic shorthair cats apart from weight, age and gen MoreThe aim of current study was comparing the diagnostic performance of computed radiography with that of analog radiography in evaluation of interstitial lung pattern based on histopathology as a gold standard. Twenty domestic shorthair cats apart from weight, age and gender differences after clinical examination were studied in lateral and ventrodorsal projections with both computed and analog radiography. Then, three radiologists independently evaluated the radiographs. Histopathology investigation used as gold standard to confirm the interstitial lung pattern detected on the radiographs. Statistical data of two radiologic approaches were analyzed by Cohen’s Kappa test and the sensitivity and specificity of each approach were also calculated. The agreement for the interstitial lung pattern was fair for both systems, but computed radiography was more sensitive. In current study the ability of computed radiography was equivalent or superior to conventional radiography for evaluation of interstitial lung pattern, since displaying more radiographic details. Accordingly, it can be a proper substitute for analog radiography considering its advantages including elimination of dark room, high contrast resolution and wide dynamic range. Manuscript profile -
Open Access Article
110 - Estimation of Inflow to Urmia Lake Using Time Series and Basin's Future Simulation Modeling in Two Long and Short Term Scenarios
اردلان شریف نسب Mojtaba ShourianThe Urmia Lake is the largest and the most important internal lake in Iran and is one of the most valuable international hemispherical resources in the world. But the Lake has been gradually getting dried nowadays. If the Lake gets completely dried, irreparable environm MoreThe Urmia Lake is the largest and the most important internal lake in Iran and is one of the most valuable international hemispherical resources in the world. But the Lake has been gradually getting dried nowadays. If the Lake gets completely dried, irreparable environmental, economical and social damages would be appeared in the region. So, finding a practical solution for surviving the Urmia Lake is crucial. In the present research, it has been tried to predict the inflows of the rivers leading to the Urmia Lake, once based on the long term period’s recorded data and another time based on the recent dry period’s recorded data, by using autoregressive moving average (ARMA) time series models in order to exert the effects of the recent drought in the forecasted data. The ARMA models are developed in the MATLAB soft ware. After calibration of the created models, the predicted discharges of the basin’s rivers were entered into the simulation model of MODSIM in order to estimate the water consumptions in the basin's future condition and finally the entering flows to the Urmia Lake in each of two forecasting scenarios. Results show that in each of two forecasting scenarios of long and short periods, the environmental water right of the lake wouldn’t be supplied totally. Also, if the agricultural water consumptions would get reduced about 14% and 56% in long and short periods respectively, the lake’s water right would be supplied completely. Manuscript profile -
Open Access Article
111 - Prediction of SPI drought index using support vector and multiple linear regressions
Saeed Samadianfard اسماعیل اسدیDrought is a natural phenomenon, which has a complex mechanism as a result of interactions of meteorological parameters and usually occurs in all climates. So, predicting drought indices and their chronological evaluation is an effective way for the drought management a MoreDrought is a natural phenomenon, which has a complex mechanism as a result of interactions of meteorological parameters and usually occurs in all climates. So, predicting drought indices and their chronological evaluation is an effective way for the drought management and adaptation with its consequences. In the current research, prediction of drought indices are carried out for Tabriz synoptic station, using support vector regression, multiple linear regression and standard precipitation index (SPI) for the time period of 1979 to 2012. In this regard, for predicting SPI indices in the periods of 3, 6, 9, 12, 24 and 48 months, six different input combinations including the antecedent correspondent values of the mentioned index have been utilized. The results of statistical analysis showed that both methods had significant accuracy. Nonetheless, the support vector regressions for predicting SPI-6, SPI-9 and SPI-24 had better performances, regarding the root mean squared errors of 0.4985, 0.4340 and 0.2427, respectively. However, the multiple linear regressions showed lower relative errors, for predicting SPI-3, SPI-12 and SPI-48. Meanwhile, it can be concluded that both examined methods including support vector and multiple linear regressions had acceptable predictions of drought index and can be used with an admissible confidentiality for the management of drought consequences. Manuscript profile -
Open Access Article
112 - Autoregressive simulation of Zarrinehrud river basin runoff using Procrustes analysis method and artificial neural network and support vector machine models
بهروز سبحانی Mohammad Isazadeh منیر شیرزادRivers flow prediction in river basins has an important role in the operation and correct management of water resources. Determining type and number of estimator models inputs is one of the important steps in rivers flow prediction. Therefore, The Procrustes analysis (P MoreRivers flow prediction in river basins has an important role in the operation and correct management of water resources. Determining type and number of estimator models inputs is one of the important steps in rivers flow prediction. Therefore, The Procrustes analysis (PA) method for determining the number of effective inputs was used. In this study, flow prediction was done using the flow data obtained from the Safakhaneh and Santeh hydrometric stations. The Artificial Neural Network (ANN) and The Support Vector Machine (SVM) models was used for flow prediction. The best estimation of flow is done using the MLP and SVM models in Safakhaneh hydrometric station with RMSE equal to 5.68 (m3/s) and 4.85 (m3/s), respectively, and CC equal to 0.73 and 0.78, respectively. While in Santeh hydrometric station RMSE was equal to 6.44 (m3/s) and 6.36 (m3/s) respectively, and CC was equal to 0.78 and 0.79 respectively for MLP and SVM models. PA-SVM model showed better results than SVM model in estimating Safakhaneh hydrometric stations flow with RMSE equal to 5.45 (m3/s) and CC equal to 0.73 during the test period. The results also indicated that SVM and PA-SVM models estimated the flow of Santeh station with RMSE equal to 6.85 (m3/s) and 7.03 (m3/s) respectively. Basically, results indicated that the Procrustes analysis method can be used as one of the Efficient and suitable methods for determining the number of effective inputs. Comparison of the ANN and SVM results indicated that ANN model has more accuracy than SVM model. Manuscript profile -
Open Access Article
113 - Assessing the Performance of WRF Model in Prediction of Evapotranspiration in Paddy Fields
Ebrahim Asadi Oskouei Mohammadreza Mohammadpour Penchah Leila Goodarzi Mojtaba ShokouhiBackground and Aim: Evapotranspiration as one of the main components of the hydrological cycle, has a significant role in proper irrigation planning and water resources management. In this case, estimating evapotranspiration is limited due to a lack of data and a defici MoreBackground and Aim: Evapotranspiration as one of the main components of the hydrological cycle, has a significant role in proper irrigation planning and water resources management. In this case, estimating evapotranspiration is limited due to a lack of data and a deficiency of meteorological stations. Therefore, today numerical models such as WRF are a powerful tool for generating and predicting meteorological quantities (wind speed, humidity, etc.) that are needed to estimate evapotranspiration. So far, no research has been conducted to investigate the effect of different schemes of the WRF model on the estimate of rice evapotranspiration. The purpose of this study is to evaluate the efficiency of the WRF model and obtain the result for estimating evaporation for rice plant in the central plain of Guilan.Method: Evapotranspiration rates vary from 2.7 to 8.5 mm per day. The average ET during three different periods of plant growth, including the initial, middle, and final periods, is estimated to be 4.63, 5.97, and 5.98 mm per day, respectively. The three configurations 1, 2, and 4 are mainly overestimated in predicting evapotranspiration of rice plants, and the computational values are estimated to be higher than the values measured by the lysimeter. The results show that the highest amount of RMSE occurred in configuration No. 4 at 8.47 and the lowest rate occurred in configuration No. 3 at 1.26. Summary of results shows that configuration No. 3 in all four criteria mentioned has performed better than other configurations to predict daily evapotranspiration of rice. The results showed that the non-local schema used in the model, simulates better than the local schemas for the daily evapotranspiration of the rice plant. Findings show that in the local YSU schema, the accuracy of predictions is significantly increased and is only 0.64 mm on average less than the estimated lysimetric data.Results: The results showed that using appropriate schemas in the surface layer and boundary layer of the WRF model, affects on accuracy of evapotranspiration predictions. The results of this study showed that, this model by using the YSU non-local boundary layer scheme can accurately predict the evapotranspiration rates of the rice plant for the next day and this is due to the higher ability of this schema in predicting the parameters affecting evapotranspiration (including temperature and wind). Therefore, the WRF model can be implemented by using GFS forecast data for the next few days and by applying the FAO-Penman-Monteith equations to the model outputs, the values of potential evapotranspiration for different regions of the country can be calculated. Since evapotranspiration is directly related to atmospheric thermodynamic processes, so using other different atmospheric physics schemas (not considered in this study) can produce different results. Manuscript profile -
Open Access Article
114 - Rainfall-Runoff modeling using Deep Learning model (Case Study: Galikesh Watershed)
Razieh Tatar Khalil Ghorbani mehdi Meftah halghi meysam salarijaziArtificial neural networks (ANN) are one of the data mining methods applied by many researchers in different fields of studies such as rainfall runoff modeling. To improve the performance of these networks, deep learning neural networks were developed to increase modeli MoreArtificial neural networks (ANN) are one of the data mining methods applied by many researchers in different fields of studies such as rainfall runoff modeling. To improve the performance of these networks, deep learning neural networks were developed to increase modeling accuracy. This study evaluated deep learning networks to improve the performance of artificial neural networks in Galikesh watershed and to predict discharge for 1, 3, 6 and 12-month time scale based on 1 to 5 month time scale lags made in precipitation and temperature data. Based on 70% and 30% of the data used for training and test respectively the results demonstrated that in all time steps, the deep learning neural network improved the performance of artificial neural network and on average RMSE decreased in both training and test from 0.68 to 0.65 and 0.84 to 0.73 respectively. Moreover, R-square was increased on average from 0.57 to 0.62 and 0.51 to 0.67 respectively in training and test. We can also denote the effect of temperature on the increase of accuracy of rainfall-runoff modeling. Manuscript profile -
Open Access Article
115 - Drought Prediction Using North American Multi-Model Ensemble (NMME) Over Western Regions of Iran
Mehdi Moghasemi Narges Zohrabi Hossein Fathian Alireza Nikbakht Shahbazi Mohammadreza YeganegiBackground and Aim: Drought as a natural hazard significantly impacts various sectors such as agriculture and water resources and causes considerable damage to these sectors worldwide. Therefore, adaptation strategies should be taken to reduce drought damage, and in the MoreBackground and Aim: Drought as a natural hazard significantly impacts various sectors such as agriculture and water resources and causes considerable damage to these sectors worldwide. Therefore, adaptation strategies should be taken to reduce drought damage, and in the meantime, planning and adaptation to drought conditions using drought forecasting is one of the most effective strategies. Due to the need for drought forecasting and the limited studies that evaluated drought indicators obtained from the rainfall forecast output from the North American Multi-Model Ensemble (NMME) in Iran. This study evaluated these models in four catchments of Karkheh, Karun, Heleh, and Hindijan-Jarahi for1982-2018.Method: In this study, the monthly output of different NMME ensembles were evaluated in the forecast leads of 0 to 9 months from 1982 to 2018, the SPI drought index was calculated. Comparison of these data with GPCC data was used for evaluation. Three quantitative criteria, including correlation coefficient, RMSE, and BIAS, were used for evaluation. Also, to integrate the existing models, two methods: a: Arithmetic mean between the existing models and B: Weighted average between the models have been evaluated by considering the correlation coefficient (CC) results. Also, two criteria (i.e., POD and FAR) and the quantitative statistical criterion (i.e., correlation coefficient) were used to evaluate the SPI drought index.Results: The results of the precipitation evaluation of the models showed that the integrated models have better performance than the individual models. In this integrated model, the weighted model also had better performance. Evaluation of spatial distribution of precipitation models also showed the excellent performance of NMME models in Karun and Hindijan-Jarahi catchments in the zero-month forecast lead and Hindijan-Jarahi catchments in the one-month forecast lead. The results of drought index evaluation showed that integrated models, although having better performance in precipitation forecasting, but in drought forecasting, the best performance belongs to NASA-GMAO-062012 and CFSv2 models. The results also showed that drought index forecasts in three and six-month periods have better performance than one month. Spatial distribution evaluation also showed that the models perform better in the southern basins. In general, it can be concluded that NMME models have good performance in predicting drought in some places and specific forecast leads, so they should be evaluated at each point before use.Conclusion: The results of precipitation evaluation showed that, in general, integrating the output of dynamic models increases its proficiency, and integration in weighted mode (WeightedNMME) performs better than the non-weighted model (NMME). According to the zero-month forecast among individual models, the NASA-GMAO-062012 model has the most skills in terms of the correlation coefficient. However, in the one-month forecast lead in terms of the correlation coefficient, RMSE and BIAS, the best performance belongs to the CFSv2 model. Evaluation of drought indices showed that the model's performance could be different from their performance in predicting rainfall. WeightedNMME, for example, performed well in NASA-GMAO-062012 and CFSv2 months, although they performed well in predicting drought. The spatial evaluation also showed that the southern catchments perform better than other basins. Manuscript profile -
Open Access Article
116 - Uncertainty Evaluation due to TIGGE Global System Precipitation Data for Flood Forecasting
Soudabeh Behiyan Motlagh Afshin Honarbakhsh Asghar AzizianBackground and Aim: The occurrence of frequent floods in Iran necessitates a flood forecasting and warning system with a suitable lead time. The use of numerical rainfall forecasting models in flood forecasting and warning is one of the important measures taken by resea MoreBackground and Aim: The occurrence of frequent floods in Iran necessitates a flood forecasting and warning system with a suitable lead time. The use of numerical rainfall forecasting models in flood forecasting and warning is one of the important measures taken by researchers in most parts of the world. The TIGGE database includes mid-term precipitation forecasts simulated by global forecast centers. The purpose of this research is to evaluate the efficiency and the degree of uncertainty caused by the rainfall forecasts of four numerical models of the TIGGE database (including CPTEC, ECCC, ECMWF, and KMA) for simulating floods with the HEC-HMS hydrological model.Methods: In this research, the precipitation data of seven meteorological stations were used to evaluate the uncertainty of discharge from TIGGE database precipitation prediction models in the Poldokhtar watershed. Also, three flood events on March 24, 2017, April 6, 2018, and April 15, 2018, were studied. At first, precipitation forecasts were extracted from four centers CPTEC, ECCC, ECMWF, and KMA. Due to the existence of systematic error in the forecasts, a bias correction was done on them, and to correct the bias, the Delta method was used. Processed and raw forecasts of four rainfall forecasting models were entered into the HEC-HMS model for flood forecasting, and in the next step, the flow uncertainty assessment of the HEC-HMS model was performed in all members of the four rainfall forecasting models. In this research, 5 factors P, R, S, T, and RD were used for uncertainty analysis.Results: The results indicate the significant superiority of the ECMWF model in predicting precipitation events. The use of all 4 rainfall sources led to an acceptable simulation of the flood peak flow in three different events. Also, the predicted peak discharge time had little difference from the observed data. According to the results of the uncertainty analysis, the ECMWF model was considered the best model based on P, R, S, T, and RD factors. The KMA model performed well in severe and very severe floods. The group prediction system of TIGGE models also had an acceptable performance in all events. Also, the hydrological-meteorological prediction model predicted the time of flood occurrence and the probability of occurrence well.Conclusion: The intended research investigates flood forecasting and warning in the Poldokhtar watershed using the meteorological-hydrological system, based on meteorological forecasts of the TIGGE database and flood simulation using the HEC-HMS hydrological model. The final product of this system is probable discharge and flood forecast. The results reveal the success of the TIGGE database in flood forecasting. The ECMWF model excelled in predicting peak discharge. The upper and lower band calculation method was used to determine the uncertainty, which showed the uncertainty well. This system displayed the time of peak discharge well and with a small time delay, which indicates its good performance. The predicted rainfall from the four centers used in this study (ECMWF, ECCC, CPTEC, and KMA) have significant differences. To reduce these differences, we used a multi-model group forecasting system that had encouraging results. Manuscript profile -
Open Access Article
117 - Comparison of Data Mining Models Performance in Rainfall Prediction Using Classification Approach (Case Study: Hamedan Airport Synoptic Weather Station)
Morteza Salehi Sarbijan Hamidreza DezfoulianBackground and Aim: Rainfall is one of the complex natural phenomena and one of the most crucial component of the water cycle, playing a significant role in assessing the climatic characteristics of each region. Understanding the amount and trends of rainfall changes is MoreBackground and Aim: Rainfall is one of the complex natural phenomena and one of the most crucial component of the water cycle, playing a significant role in assessing the climatic characteristics of each region. Understanding the amount and trends of rainfall changes is essential for effective management and more precise planning in agricultural, economic, and social sectors, as well as for studies related to runoff, droughts, groundwater status, and floods. Additionally, rainfall prediction in urban areas has a significant impact on traffic control, sewage flow, and construction activities. Method: The objective of this study is to compare the accuracy of classification models, including Chi-squared Automatic Interaction Detector (CHAID), C5 decision tree, Naive Bayes (NB), Quest tree, and Random Forest, k-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Artificial Neural Network (ANN) in predicting rainfall occurrence using 50 years of data from the synoptic station at Hamedan Airport. In this study, 80% of the data is used for training the models, and 20% for model validation and the results obtained from the model executions are compared using metrics such as confusion matrix, Receiver Operating Characteristic (ROC) curve, and the Area Under the Curve (AUC) index. To create the classification variable for rainfall and non-rainfall data, based on rainfall data, the days of the year are categorized into two classes: days with rainfall (y) and days without rainfall (n). Data preprocessing is performed using Automatic Data Preprocessing (ADP). Then, Principal Component Analysis (PCA) is employed to reduce the dimensions of the variables. Results: In this study, the PCA method reduces the dimensions of the variables to 5. Also, approximately 80% of the available data corresponds to rainless days, while 20% corresponds to rainy days. The research results indicated that the KNN model with an accuracy of 91.9% for training data and the SVM model with 89.13% for test data exhibit the best performance among the data mining models. The AUC index for the KNN model is 0.967 for training data and 0.935 for test data, while for the SVM algorithm, it is 0.967 for training data and 0.935 for test data. According to the ROC curve for Hamedan rainfall data, the KNN model outperforms other models. Considering the sensitivity index in the confusion matrix, the KNN and SVM models perform better in predicting non-rainfall occurrence for training data. In terms of the precipitation occurrence prediction, the RT and KNN models show better results according to the specificity index. Conclusion: The results demonstrated that for the RT, C5, ANN, SVM, BN, KNN, CHAID, QUEST, accuracy metrics was obtained 86.82%, 89.78%, 89.55%, 89.96%, 88.06%, 91.9%, 88.29%, 87.46%, 91.9%, respectively for training data. Moreover, for test data, the accuracy metrics for this model was obtained 83.82%, 87.9%, 88.12%, 89.13%, 87.12%, 89.13%, 87.12%, 88.19%, 86.93%, 86.76%, respectively. The AUC index in the training data for RT, C5, ANN, SVM, BN, KNN, CHAID QUEST models was 0.94%, 0.99%, 0.94%, 0.94%, 0.93%, 0.97%, 0.93%, 0.89%, respectively. In addition, for the test data, this metric was evaluated 0.89%, 0.89%, 0.93%, 0.94%, 0.92%, 0.90%, 0.92%, 0.88% respectively. As observed, considering accuracy metric and AUC index for training data KNN model and for test data SVM model were more sufficient in rainfall prediction. Manuscript profile -
Open Access Article
118 - Drought Forecasting Using Wavelet - Support Vector Machine and Standardized Precipitation Index (Case Study: Urmia Lake-Iran)
Mehdi Komasi Soroush SharghiBackground and Objectives: Drought is regarded as a serious threat for people and environment. As a result, finding some indices to forecast the drought is an important issue that needs to be addressed urgently. The appropriate and flexible index for drought classificat MoreBackground and Objectives: Drought is regarded as a serious threat for people and environment. As a result, finding some indices to forecast the drought is an important issue that needs to be addressed urgently. The appropriate and flexible index for drought classification is the Standardized Precipitation Index (SPI). Artificial intelligence models were commonly used to forecast SPI time series. These models are based on auto regressive property. So, they are not able to monitor the seasonal and long-term patterns in time series. In this study, the Wavelet-Support Vector Machine (WSVM) approach was used for the drought forecasting through employing SPI. Method: In this way, the SPI time series of Urmia Lake watershed was decomposed to multiple frequent time series by wavelet transform; then, these time series were imposed as input data to the Support Vector Machine (SVM) model to forecast the drought. Findings: The results showed that, the maximum value of R2 and minimum value of RMSE indexes for SVM model are 0.865 and 0.237 and for WSVM model are 0.954 and 0.056 respectively in verification step. Discussion and Conclusion: So, the propounded hybrid model has superior ability in forecasting SPI time series comparing with the single SVM model and also it can accurately assess the extreme data in SPI time series by considering the seasonality effects. Finally, it was concluded that, the proposed hybrid model is relatively more appropriate than classical autoregressive models such as ANN. Manuscript profile -
Open Access Article
119 - Forecasting Municipal Solid Waste Quantity by Intelligent Models and Their Uncertainty Analysis
Maryam Abbasi Malihe Fallah Nezhad Rooholah Noori Maryam MirabiBackground and Objective: The first step in design of municipal waste management systems is complete understanding of waste generation quantity. Forecasting waste generation is one of the most complex engineering problems due to the effect of various and out of control MoreBackground and Objective: The first step in design of municipal waste management systems is complete understanding of waste generation quantity. Forecasting waste generation is one of the most complex engineering problems due to the effect of various and out of control parameters on waste generation. Therefore, it is obvious that it is necessary to develop approaches to a model such complex events. The objective of this study is forecasting waste generation quantity using intelligent models as well as their comparisons and uncertainty analysis.Method: In this study, Mashhad city was selected as a case study and waste generation time series of waste generation in 1380 to 1390 were used for weekly prediction. Intelligent models including artificial neural network, support vector machine, adaptive neuro-fuzzy inference system as well as K-nearest neighbors were used for modelling. After optimizing the models’ parameters, models’ accuracy were compared by statistical indices. Finally, result uncertainty of the models was done by Mont Carlo technique.Findings: Results showed that coefficient of determination (R2) of artificial neural network adaptive neuro-fuzzy inference system, support vector machine, and K-nearest neighbor models were 0.67, 0.69, 0.72 and 0.64 respectively. Uncertainty analysis was also justified the results and demonstrates that support vector machine model had the lowest uncertainty among other models and the lowest sensitivity to input variables.Conclusion: Intelligent models were successfully able to forecast waste quantity and among the studied models, support vector machine was the best predictive model. Moreover, support vector machine produced the results with the lowest uncertainty the other models. Manuscript profile -
Open Access Article
120 - Optimization and Prediction Changes of Groundwater Quality Parameters Using ANN+PSO and ANN+P-PSO Models (Case Study: Dezful Plain)
Fahimeh Sayadi Shahraki Abdolrahim hooshmand Atefeh Sayadi ShahrakiBackground and Objective: One of the main aims of water resource planners and managers is the estimation and prediction of groundwater quality parameters to make managerial decisions. In this regard, many models have been developed which proposed better managements in o MoreBackground and Objective: One of the main aims of water resource planners and managers is the estimation and prediction of groundwater quality parameters to make managerial decisions. In this regard, many models have been developed which proposed better managements in order to maintain water quality. Most of these models require input parameters which are hardly available or their measurements are time consuming and expensive. Among them, Artificial Neural Network (ANN) models inspired by human's brain are a better choice.Method: The present study stimulated the groundwater quality parameters of Dezful plain including Sodium Adsorption Ratio (SAR), Electrical Conductivity (EC), Total Dissolved Solids (TDS), using ANN+PSO and ANN+P-PSO models and in the end is comparing their results with measured data. The input data for TDS quality parameter consist of EC, SAR, pH, SO4, Ca, Mg and Na, for SAR including the TDS, pH, Na, Hco3 and quality parameter of EC contains So4, Ca, Mg, SAR and pH, gathered from 2011 to 2015.Findings: The results indicated that the highest prediction accuracy of quality parameters of SAR, EC and TDS is related to the ANN+P-PSO model so that the MAE and RMSE statistics have the minimum and has the maximum value for the model. The results showed that RMSE for PSO in predicting SAR, EC and TDS were 0.09, 0.045 (µs/cm) and 0.053 (mg/l) in testing period, respectively. These statistical criteria were 0.039, 0.031 (µs/cm) and 0.045 (mg/l) for P-PSO in this period, respectively.Discussion and Conclusion: The results showed that P-PSO had more accuracy compared to PSO. In addition, there were no significant differences between ANN and collecting values. So, it is recommended that ANN were applied to determine nitrate concentration in groundwater. Manuscript profile -
Open Access Article
121 - Investigating the Role of Global Warming on Wind Speed and Sea Level Pressure Fluctuations in Sistan Region
Esmaeil Poudineh Broumand Salahi Mahmoud Khosravi Mohsen HamidianpourBackground and Objective: The temporal variability of local winds of Sistan during the period of global warming is the subject of this research. In recent decades, global warming has brought about tangible changes in the temperature of the planet and has influenced othe MoreBackground and Objective: The temporal variability of local winds of Sistan during the period of global warming is the subject of this research. In recent decades, global warming has brought about tangible changes in the temperature of the planet and has influenced other atmospheric parameters such as wind speed. Method: In the study of atmospheric parameters, estimating the effect of global warming on these parameters is important. For this purpose, variations in the Sistan wind speeds and sea level pressure in the study area under the conditions of the two scenarios A2 and B2 from the output of the global Hadcm3 model were downscaled and for three periods of 30 years up to 2099, the changes in these two parameters were generated and examined. Findings: The results showed that the average wind speed calculated by scenario B2 for the period 2010-2039, 2040-2069 and 2070-2070 respectively 0.67, 0.88 and 1.15 m / s Relative to the Basic course will increase. Also, the average wind speed variation under A2 scenario Conditions, which is a pessimistic scenario, is 1.36 and 1. 57 and 1.79 m / s for the periods 2039-2039 and 2069-2070 and 2070-2070 Also, the pressure calculated by scenario B2 for the period 2010-2039, 2040-2069, and 2070-2070 will be reduced to 0.04, 0.10, and 0.16, respectively, compared to the base period. Discussion and Conclusions: The results showed that the decline in pressure and increase in wind speed has not been uniformly distributed throughout the year. However, during the winter and spring and summer, pressure drop is more regular than the autumn season. Manuscript profile -
Open Access Article
122 - Prediction Impact of Climate Change on the Temperature & Precipitation by General Circulation Model, a Strategy for Sustainable Agriculture: (Case of Kermanshah Township)
Samireh Seymohammadi Mohsen Tavakoli Kiumars Zarafshani Hossien Mahdizadeh Farzad AmiriBackground and Objectives: Concern about climate change and its effects on various aspects of human life in general and agricultural production in particular is growing. Therefore, the main purpose of this study is to assess and predict of climate change induced tempera MoreBackground and Objectives: Concern about climate change and its effects on various aspects of human life in general and agricultural production in particular is growing. Therefore, the main purpose of this study is to assess and predict of climate change induced temperature and precipitation of Kermanshah township.Method: The calibration and validation of the HadCM3 model was performed 1961-2001 of daily temperature and precipitation. The data on temperature and precipitation from 1961 to 1990 were used for calibration whereas data from 1991 to 2001 were used for model validation. SDSM version 4.2 as a downscaling model used to downscale general circulation models to station scales. Findings: The least difference between observed data and simulation data during calibration and validation showed that the parameter was precisely modeled for most of the year. This study under A2 scenario, three time periods (2020, 2050, 2080) were simulated. Discussion and Conclusion: According to our simulated model, precipitation showed a decreasing trend whereas temperature showed an increasing trend. The result of this study can also be used as an optimal model for land allocation in agriculture. Manuscript profile -
Open Access Article
123 - Surveying and Predicting Surface Currents of Khuzestan Province Using Time Series Models
Alireza Entezari Rasoul SarvestanThe purpose of this study was to study the surface currents of Khuzestan province and its prediction for the period (2019Background and Objective: The present study is to evaluate the surface currents of Khuzestan province and its forecast for the period 2019 to 2021 us MoreThe purpose of this study was to study the surface currents of Khuzestan province and its prediction for the period (2019Background and Objective: The present study is to evaluate the surface currents of Khuzestan province and its forecast for the period 2019 to 2021 using time series models.Material & Methodlogy: The present study was conducted in 9 selected stations from Khuzestan province in order to compare the accuracy of the time series model and predict the amount of surface currents. For this purpose, the monthly flow data of the hydrometric station for 22 years (1391-2014) has been used. The multiplicative seasonal time series model of surface currents was investigated and the best model was fitted. Findings: The results of these studies show that the best models fitted in SARIMA (1,1,1) (1,0,1), SARIMA, SARIMA (0,1,1) (1,0,1), telephoto SARIMA, Primate (1,0,1) (1,1,1) SARIMA, Dezful (1,0,2) (1,1,1) SARIMA, Plain SARIMA, Dokehe (0,2,2) (1,1,1) SARIMA, Gotvand (1,1,2) (1,0,1) SARIMA (1,1,1) And SARAB (1.1.2) (2.1.1), which had good accuracy to predict surface currents.Discussion and Conclusion: Surveying the annual prediction of surface currents for 2019 to 2029 showed that surface currents in all selected stations decreased and this decrease in Ahwaz station to the highest and the two-hill station to the lowest values reaches to 9.78 and 0/58 respectively; also, the monthly forecast showed that in December, with 6/98 and 1/67, the highest and lowest decreases would occur. Manuscript profile -
Open Access Article
124 - Analysis of the Impact of In-Between Meaning on Promoting the Sense of Place in the Qajar Mosque-Schools (Case Study: Salehiye Mosque- School in Qazvin City) *
Samin Torkaman Jamaleddin SoheiliBackground and Objective: In the architecture of Islamic period of Iran, public buildings such as mosques-schools were places for people to interact with different tastes and thoughts, with their diverse functions and spaces and with in-between spaces that played a deci MoreBackground and Objective: In the architecture of Islamic period of Iran, public buildings such as mosques-schools were places for people to interact with different tastes and thoughts, with their diverse functions and spaces and with in-between spaces that played a decisive role in organizing the diverse functions of these places and linking them more closely. They formed a whole, and made it possible for one to stay in that place. The purpose of this study is to investigate the effect of the in-between spaces on promoting a sense of place in the Qajar mosque-schools and to explore how in-between spaces can be effective in promoting a sense of place?Method: Correlation analysis in Spss software was used to analyze the variables, and with library, field and survey studies to investigate the effective factors in promoting sense of place and in-between spaces.Findings: Results of this study indicate that the coefficient of significance between the variables of sense of place and in-between spaces is less than 0.05 and there is a significant relationship between these two variables.Discussion and Conclusion: The use of in-between spaces can be effective in creating sense of place in architectural space. Because today the concept of in-between spaces is very important in the design of architectural spaces, so that it can be used to reinforce the link between human and place in new public spaces, ultimately leading to better exploitation of the environment and the continued presence of people. Manuscript profile -
Open Access Article
125 - Ground Water Modeling to Estimate Nitrate Dispersion in Critical Aquifers (A Case Study: Mashhad City)
Akbar Baghvand Ali Vosoogh Saeed Givehchi Ali Daryabeigi ZandAt present, due to inefficient and incorrect management, most domestic aquifers in Iran, particularly in dry regions, including the Mashhad plain, face lowering levels of lakes and ponds in water storage and are sometimes subject to various pollutants. In fact, a main a MoreAt present, due to inefficient and incorrect management, most domestic aquifers in Iran, particularly in dry regions, including the Mashhad plain, face lowering levels of lakes and ponds in water storage and are sometimes subject to various pollutants. In fact, a main and significant index which shows the aquifers infections is that nitrate is found in water. In this research, an attempt has been made to prepare a mathematical model for qualitative and quantitative value of the Mashhad plain aquifer. Consequently, the aquifer’s behavior is predicted and simulated based on nitrate ion during the last twelve years. In order to develop a mathematical model for qualitative and quantitative value of Mashhad plain’s aquifer, meteorological, hydrological and hydro geological data and statistics were analyzed using Surfer Ver. 8 software, computer code Modflow 2000 and GMS processor. After calibration settings and verification, this mathematical model is achieved. Results indicate that in the year 2022 the problematic issue of nitrate infections will remain intact for most central and eastern parts of the Mashhad aquifer and its density in these regions varies from 10 to 90mg. Based on this information, in most regions nitrate density is more than the permitted amount (45mg per liter) and the annual mean drop value for this aquifer (0.90 meter) shows its critical situation. The main reason for this aquifer’s pollution during recent years is non-standard waste gathering and sewage burying methods and combination with water wells, thus its penetration through these water wells into the aquifer. Manuscript profile -
Open Access Article
126 - Comparison of Autoregressive Static and Artificial Dynamic Neural Network for the Forecasting of Monthly Inflow of Dez Reservoir
Mohammad Ebrahim Banihabib Mohammad Valipoor S. Mahmood BehbahaniIn this paper, the capability of autoregressive static and artificial dynamic neural networks models was compared for forecasting of monthly inflow of Dez reservoir. In previous researches, static and artificial dynamic neural networks models have not been compared MoreIn this paper, the capability of autoregressive static and artificial dynamic neural networks models was compared for forecasting of monthly inflow of Dez reservoir. In previous researches, static and artificial dynamic neural networks models have not been compared for above-mentioned propose. In addition, using artificial neural network model as an autoregressive model is innovation point of this research. Monthly flow data of Dez station in Dez River in years1955 to 2001 is used in this research. Data of 42 former years and 5 recent years are used for Training and testing data set, respectively. Different structure for the static and artificial dynamic neural network models were evaluated by comparing the root-mean-square error (RMSE) of the models. First, static and artificial dynamic neural network models were selected in training phase using data from October 1955 to September 1997. Then, using the selected structures, the monthly forecasted inflow of reservoir was compared with observed data from October 1997 to September 2001. Also, two types of radial and sigmoid activation function and the number of neurons in the hidden layer were investigated in this study. Results showed that the best model to forecast the reservoir inflow is autoregressive artificial neural network model associated with the sigmoid activation function and 17 neurons in the hidden layers. Artificial dynamic neural network model with sigmoid activation function can forecast reservoir inflow for 5 years better than static artificial neural networks model Manuscript profile -
Open Access Article
127 - Prediction of Carbon Monoxide Concentration in Tehran using Artificial Neural Networks
Hamid Reza Jeddi Rahim Ali Abbaspour Mina Khalesian Seyed Kazem AlavipanahBackground and Objective: Nowadays, air pollution is one of the most important problems almost all over the world. There are many strategies to control and reduce air pollution, one of which is prediction of this event and getting ready to deal with the negative effects MoreBackground and Objective: Nowadays, air pollution is one of the most important problems almost all over the world. There are many strategies to control and reduce air pollution, one of which is prediction of this event and getting ready to deal with the negative effects of it. The aim of this study is to provide a multi-layer structure of artificial neural networks (ANN) for predicting of carbon monoxide pollution at subsequent 24 hours in Tehran metropolis. Method: To predict the amount of CO emissions in near future (subsequent 24 hours), wind speed and direction, temperature, relative humidity, and barometric pressure characteristics are used as meteorological data, and concentration of carbon monoxide is considered as a pollution parameter. To eliminate the noise of data, wavelets transform method and determining the threshold with normal distribution are used before training the ANN. Finally, two neural networks as two general models are proposed and used for modelling. Findings: The results show that the correlation coefficient, index of agreement, accuracy of prediction, and root mean square error for model no. 1 with duplicate data are 0.9012, 0.915, 0.848, and 0.1012 and for model no. 2 with duplicate data are 0.9572, 0.978, 0.963, and 0.0385 respectively. Moreover, the results of listed parameters for model no. 1 with new data are 0.9086, 0.89, 0.885, and 0.0825 and for model No. 2 with new data are 0.8678, 0.928, 0.932, and 0.1163 respectively. Conclusion: Results showed that there is a good agreement between predicted and observed values, hence the proposed models have a high potential for air pollution prediction. Manuscript profile -
Open Access Article
128 - Modeling and Forecasting Air Pollution of Tehran Application of Autoregressive Model with Long Memory Properties
reza akhbari Hamid AmadehBackground and Objective: Environmental pollution modeling is one of the essential requirements in the field of air quality monitoring which with using the output of the model, improvement of future situation can be possible. The existing literature of the modeling of e MoreBackground and Objective: Environmental pollution modeling is one of the essential requirements in the field of air quality monitoring which with using the output of the model, improvement of future situation can be possible. The existing literature of the modeling of environmental pollution –especially air pollutants- could be divided to two whole categories. First, those researches that in addition of pollutants data, they used some factors such as temperature, wind direction, wind speed and humidity. The second one –which this study belong to- with using time series regression models and by usage of the existing data about each pollutant, the future situation was forecasted. Method: In this study, we forecast future pollutants (CO,PM10,NO2,SO2,O3,PM2.5) status with ARIMA, ARFIMA and ARIMA-GARCH models with Box-Jenkins approach, then the best model is determined with MSE, RMSE, MAE and MAPE. Findings: Results indicate that the assumption of existence of long-memory is acceptable but the hypothesis that always ARFIMA models prepare the best forecast is rejected. Discussion and Conclusion: This study proves the application of econometric models to predict the pollutants state. Based on the high social costs of pollutant emissions, it is recommended that using these models, identify the pollutants affecting the future of the city and reduce the level of their dissemination of efficiency plans. Manuscript profile -
Open Access Article
129 - Using dynamic recurrent neural network NAR for predicting monoxide carbon concentration
Mehrdad Rafiepour Ali Asghar Alesheikh Abbas Alimohammad Abolghasem Sadeghi NiarakiBackground and Objective: Air pollution is one of the most important problems in big cities. One of the goals of urban managers is their awareness on air pollution in the future. For prediction of air quality, air pollutant must be modeled first. Carbon monoxide is one MoreBackground and Objective: Air pollution is one of the most important problems in big cities. One of the goals of urban managers is their awareness on air pollution in the future. For prediction of air quality, air pollutant must be modeled first. Carbon monoxide is one of the most toxic air pollutants that has harmful effect on human health. Method: In this paper, modeling carbon monoxide concentration and 24-h prediction by ARMA and NAR neural network have been studied. Then, the results of the two methods are compared. For this purpose, data is collected on 29 November until 31 December 2009 in Azadi air quality monitoring station: belonged to Tehran department of environment. Findings: The results of the two methods showed that, NAR is more accurate than ARMA for modeling and prediction of carbon monoxide. NAR neural network had MSE=1.6 and a correlation coefficient of 0.84 while ARMA had MSE=5.46 and correlation coefficient=0.72 for 24 hours prediction. Discussion and Conclusion: Finally, the predicted values can be used and published in internet for public awareness. Also urban managers can use the results of modeling and prediction for a better management. Result of this paper showed NAR neural network has sufficient ability to model and predict time series of monoxide carbon Manuscript profile -
Open Access Article
130 - Study of Environmental Impact of Minab Esteghlal Dam in Operation Phase Using a Combination of Modified and ICOLD Methods
Seyed Ali Jozi Leila Hosseini Ali DehghaniBackground and Objective: Minab Esteghlal dam, with a capacity of 350 million m2 and an efficient capacity of 270 million m2, is a stable-weight-concrete dam which is constructed on Minab river at the distance of 4 km from the east of Minab township with a geographic lo MoreBackground and Objective: Minab Esteghlal dam, with a capacity of 350 million m2 and an efficient capacity of 270 million m2, is a stable-weight-concrete dam which is constructed on Minab river at the distance of 4 km from the east of Minab township with a geographic longitude of 57° and 4′ and a geographic latitude of 27° and 9′. This dam was established in 1993 to supply the drinking water for Bandar Abbas and to provide water for 14670 hectares of downstram lands in Minab and for industry, flood control and artificial nutrition purposes. Method: This study is carried out to analyze the environmental impacts caused by operation of the dam. After collecting the basic data and field survey of the site and the dam reservoir, a list of environmental resources being affected was prepared. The study area was also determined in the from of individual environment under the direct and indirect impacts. Then, the required maps for the site, stations, ground cover, etc, were provided in the GIS environment. Water sampling was accomplished in warm and dry and warm and humid seasons, and water samples were carefully examined. In order to predict the dam impacts, a special method of assessment called ICOLD was conducted. After determining all the impacts, since this method is a qualitative method, a modified method was used to mark and interprete the impacts. Results: The results of this study showed that Esteghlal dam had a positive impact on biologic and socio-economic environments and had the scores of +207.5 and +329.25, and had a negative impact of -242 on physico–chemical environment. At the end, some recommendations to eliminate the negative impacts caused by operation of the dam, including decrease of deposit input to the river via constructing som dams at the upperhills before Esteghlal dam, and propagation of biological methods instead of applying fertilizer to defeat the agricultural pests were suggested. The proper environmental management of Minab watershed is bound to careful implementation of these suggestions. Manuscript profile -
Open Access Article
131 - The Role of In-Between Space in the Spatial Organization of Urban and Architectural Elements. Case Study: Tabriz City in Ghajar Period
Lida Balilan Asl Dariush sattarzadehIntroduction: One of the major problems in the fabric of most cities in the world, is the crisis in theidentity of urban and architecture. The physical display of the identify crisis in the cities is the spatialseparation of the architectural and urban elements, in the MoreIntroduction: One of the major problems in the fabric of most cities in the world, is the crisis in theidentity of urban and architecture. The physical display of the identify crisis in the cities is the spatialseparation of the architectural and urban elements, in the particular and whole scales. As to the claimof this paper, an ignorance of the connective and in-between spaces is an important and impressivefactor in the physical identity crisis of the historical fabrics.Material and method: To obtain the mentioned objectives and to prove the hypothesis of theresearch, a phenomenological approach and historical analysis method are used to analyze the contentof the texts.Result & Discussion: The obtained results suggest that the in-between space due to its constructiveobjectives takes on an equivocal nature. It becomes both the process and the product. Thus, itcontributes to the formation process in order that a unified whole should emerge; it also helpssimultaneously the concepts be classified and take orientation. Therefore, in a rotational movement thein-between space influences the spatial organization through its impact on the basics and principles.On the other hand, through its spatial features such as space relations, the spatial organization isinfluential in the development and evolution of the in-between spaces. The result emphasizes on thecomprehensibility of the in-between spaces in the various urban and architectural scales, andconsequently it puts emphasis on the significance of the in-between spaces as the major factors in thespatial organization. Manuscript profile -
Open Access Article
132 - Developing an Optimal Method for Financial Distress Prediction of the Firms (Case Study: Tehran Stock Exchange)
Mansour Soufi Mahdi Homayounfar Mehdi FadaeiOne of the most important issues in the field of financial management is how the investors distinguish between favorable investment opportunities and undesirable ones. One of the ways to help investors is to provide financial distress prediction models. According to the MoreOne of the most important issues in the field of financial management is how the investors distinguish between favorable investment opportunities and undesirable ones. One of the ways to help investors is to provide financial distress prediction models. According to the various studies have been made to develop these type of models, in this study the combination of artificial neural networks (ANN) and genetic algorithm (GA) techniques based on Zimensky prediction ratios is used for modeling financial distress. The research statistical population includes public companies in Tehran stock exchange which admitted between October 2013 to October 2015 and among them 66 distressed and 150 going concern companies were selected as the research sample using screening method. The results indicate that the power of both artificial neural network and genetic algorithm models in financial distress prediction are equal (95 percent), however, the prediction error of neural network is relatively low compared to genetic algorithm. Manuscript profile -
Open Access Article
133 - Structural modeling of the precondition of financial behavior of investors in Iran’s stock market
Fatemeh Ahmady Mehrdad Ghanbari babak Jamshidinavid Shahram MamiThis study followed the design of a model to predict the financial behavior of investors in the Iranian stock market. Qualitative content analysis of scientific texts related to the research topic was used to identify the criteria. Interactive matrix and based on expert MoreThis study followed the design of a model to predict the financial behavior of investors in the Iranian stock market. Qualitative content analysis of scientific texts related to the research topic was used to identify the criteria. Interactive matrix and based on expert opinion based on interpretive structural modeling method was developed and a five-level model was obtained. To determine the type of variables, the MicMac analysis was used. In the five-level model of this study the variables of informal news, investor financial conditions, subjective financial knowledge, and herd behavior at the fifth level were the most influential and believable, personal judgment, emotion control, and loss aversion were the most influential variables of this model at level one of this model, were affected. MicMac analysis also indicated that the variables of informal news, subjective financial knowledge, investor financial conditions, self-esteem, and herd behavior were independent, and the variables of avoidance, believability, financial technology, emotional control, personal judgment, and financial specialties are also type dependent and other variables are interface type. Manuscript profile -
Open Access Article
134 - Application of Genetic Algorithm, Particle Swarm and Artificial Neural Networks in Predicting Profit Manipulation
Morteza Hoseinalinezhad Seyed Mohamad Hassan Hashemi Kucheksarai Ali JafariProfit management has been one of the most controversial topics in recent research. Most research on earnings management has examined the linear relationship between independent variables and earnings management using statistical methods but they did not use these varia MoreProfit management has been one of the most controversial topics in recent research. Most research on earnings management has examined the linear relationship between independent variables and earnings management using statistical methods but they did not use these variables to predict earnings management. Today, with the growth of information technology and the introduction of artificial intelligence, including artificial neural networks into the field of scientific research, it has become possible to study nonlinear relationships between variables. In this study, an attempt was made to estimate optional accruals for predicting earnings management using artificial neural networks. Also in this research, the genetic algorithm optimizer model and Particle swarm has been used to optimize the weights of the artificial neural network model to enhance the predictive power. Then, the ability to predict profit management was evaluated using the modified Jones statistical model, artificial neural network and the combined technique of genetic algorithm, Particle swarm and neural network. The sample used in this study included 150 companies listed on the Tehran Stock Exchange between 2015 and 2020. Findings showed that the artificial neural network has a high ability to predict profit management, compared to the modified Jones linear model. The findings also indicate that the accuracy and ability of the combined model of genetic algorithm, particle swarm and neural network in predicting profit management is higher than the combined model of genetic algorithm-artificial neural network. Manuscript profile -
Open Access Article
135 - Predicting Customer Churn in the Insurance Industry: Identifying the Influential Factors
samaneh soltani Lifshagerd Kambiz Shahroodi Ebrahim ChiraniIran insurance industry has recently faced with various problems regarding fluctuations in profitability, portfolio composition, the rate of loss, the rate of penetration, retention and satisfaction of insurers and market share, due to presence of numerous insurance com MoreIran insurance industry has recently faced with various problems regarding fluctuations in profitability, portfolio composition, the rate of loss, the rate of penetration, retention and satisfaction of insurers and market share, due to presence of numerous insurance companies in the competitive market. As a result, insurer maintenance has become a major goal for most of the insurance companies. Since in the insurance industry, like many other industries, the cost of searching for new insurers is far more expensive than retaining the current insurers, it is essential to identify the factors that drive insurers to churn. The purpose of this study is to investigate the literature and research background in the field of customer churn, which ultimately leads to identifying and classifying “influential factors in predicting customer churn in the insurance industry”. A systematic literature review method is used to collect and review previous studies by integrating automated and manual search strategies of all the related research articles in this field, published for the period 1389 to 1398 for Persian articles and 2010 to 2018 for English articles. The research findings identified 85 factors that affect customer churn, specifically in the insurance industry. They are classified into four categories; the factors related to the insurer, the factors related to the insuree, product/service related factors and factors regarding the relationship between the insurer and the insuree. Manuscript profile -
Open Access Article
136 - Nonparametric model test by using adaptive group LASSO method to identify the effective features in predicting the expected returns of stock portfolios
Raheleh ossadat Mortazavi Hamidreza Vakilifard Ghodratallah Talebnia seyedeh mahboobeh jafariIn this paper, a new nonparametric method is applied using the adaptive group LASSO for selecting features and studying which of the features provide incremental information for predicting the cross-sectional expected return. Out of many features mentioned in previous s MoreIn this paper, a new nonparametric method is applied using the adaptive group LASSO for selecting features and studying which of the features provide incremental information for predicting the cross-sectional expected return. Out of many features mentioned in previous studies, the effect of 36 characteristics on the expected returns of stock portfolios in Tehran Stock Exchange (1396-1387) was investigated.The result of this study shows that only three to five features provide incremental information to predict the expected return on stock portfolios. Therefore, only the return characteristics of 2 to 1 month before the forecast, total fluctuations, beta, maximum daily returns, and the ratio of price to the highest price have the power to predict the expected return on stock portfolios. The rest of the studied features do not have the power to predict expected returns. Manuscript profile -
Open Access Article
137 - Designing a model for forecasting the return of the stock index (with emphasis on neural network combined models and long-term memory models)
Reza Najarzadeh Mehdi Zolfaghari Samad GolamiThis study presents the new hybrid network of GARCH family and an artificial neural network to predict the Tehran Stock Exchange index during the period of 2008-2017. The existence of long-term memory in the conditional variance of the Tehran stock returns causes use in MoreThis study presents the new hybrid network of GARCH family and an artificial neural network to predict the Tehran Stock Exchange index during the period of 2008-2017. The existence of long-term memory in the conditional variance of the Tehran stock returns causes use in addition GARCH and EGARCH models with short- memory, long-term memory models. In addition to long-term memory models, considering the better performance of hybrid models in predicting financial data of the Garch family models (short and long-term) are combined with the artificial neural network. Using hybrid models the return of stock index was forecast for the next 10 days and its accuracy was evaluated using the evaluation criteria. The results showed that the hybrid FIEGARCH with the student-t distribution model was more efficient in forecasting return of stock and had a lower forecast error than others models Manuscript profile -
Open Access Article
138 - Investigate the Effect of Prediction Profit Reporting Tone on Investors' Reactions and Performance Prediction
mahmoud toorchi Mahmoud Lari Dashtebayaz Mohammad Reza RazdarIn recent years, the analysis of various aspects of qualitative information on financial reports is one of the important tools for decision making by investors and other capital market users. The purpose of this study, was to investigate The effect of the earnings forec MoreIn recent years, the analysis of various aspects of qualitative information on financial reports is one of the important tools for decision making by investors and other capital market users. The purpose of this study, was to investigate The effect of the earnings forecast report tone on investor response and performance prediction. To investigate this issue, the present study uses 140 years- company listed companies at Tehran Stock Exchange between 2011 and 2017. In order to test the hypotheses of the research, multiple regression and logistic regression were used. The research findings suggest that earnings forecast report tone is not a suitable tool for investors and other users to predict future earnings and future cash flows (future performance). Also, no significant relationship was found between the earnings forecast report tone with some of the incremental (decreasing) criteria of managers' understanding to manage the report tone, such as renewing the presentation of profits and realizing the near real. In other words, the earnings forecast report tone does not have any effect on the perception and awareness of the investors. Manuscript profile -
Open Access Article
139 - A Model to Predict Bankruptcy using the Mechanisms of Corporate Governance and financial ratios
ghazaleh Alibabaee Hamed KhanmohammadiImproving the economic and business environment is the most important factor in preventing bankruptcy, therefor, Artificial intelligence uses to predict the bankruptcy of companies in the future. In this study, companies in the Tehran Stock Exchange over a period of 10 MoreImproving the economic and business environment is the most important factor in preventing bankruptcy, therefor, Artificial intelligence uses to predict the bankruptcy of companies in the future. In this study, companies in the Tehran Stock Exchange over a period of 10 years in terms of bankruptcy localized model of Kurdistani-Tatli based on the Altman model were examined and companies were identified as bankrupt and healthy. Research data were collected, categorized and refined using secondary data extracted from financial statements and through the database of the Exchange Organization and the Central Bank.The models used to evaluate the data and predict the bankruptcy of companies are artificial intelligence models . Artificial neural network, combination of neural network and genetic algorithm and the K-nearest neighbor method has been used. They were also compared in terms of prediction accuracy. The output of the models indicates that the addition of corporate governance indicators to the financial ratios indicators has not improved the results. Therefore, financial ratios alone are sufficient for predicting and determining bankruptcy. The proposed model of this research based on accuracy is a combined model of neural network and genetic algorithm that has the highest accuracy. Genetic algorithm improves the optimal results of the neural network and provides a more optimal answer. Manuscript profile -
Open Access Article
140 - Liquidity and Information Efficiency in Cryptocurrencies Market
Mohammad SalehifarIn this paper, we evaluate the behavior of return, liquidity, and information efficiency in cryptocurrencis market. Cryptocurrencis are a kind of virtual currencies which cryptography technology is a basic element in their designing. They are often managed in an undistr MoreIn this paper, we evaluate the behavior of return, liquidity, and information efficiency in cryptocurrencis market. Cryptocurrencis are a kind of virtual currencies which cryptography technology is a basic element in their designing. They are often managed in an undistributed manner. The sample consists of 13 cryptocurrencies which were traded during 3 years (11/1/2015 until 11/1/2018) consistently. We apply Dickey-Fuller test, Ljung-Box autocorrelation parametric test, Fama-French autocorrelation test, Run and Hurst non-parametric tests to explore momentum and long-run memory in cryptocurrencis market. Findings show that cryptocurrencis return has an unpredictable behavior in markets which are more liquid. Indeed, liquidity has a direct relationship with information efficiency in cryptocurrencis market. Totally, the more liquid cryptocurrencis markets are, the less return predictability will be happened and cryptocurrencis return time series will move to a random walk. Therefore, the efficient market hypothesis will be improved. Manuscript profile -
Open Access Article
141 - Systemic risk assessment models: a better approach in Iranian financial institutions
majid noroozi Hamid Reza Kordlouei Reza gholamijamkarani hossein Jahangirniaریسک سیستمیک به خطر شکست سیستم مالی یا شکست کل بازار اطلاق میشود. این ریسک میتواند از بیثباتی یا بحران در مؤسسات مالی نشأت بگیرد و در اثر سرایت به کل نظام مالی انتقال یابد. بهعبارتی ریسک سیستمیک به میزان به همپیوستگی در یک سیستم مالی اشاره دارد جاییکه شکست در یک Moreریسک سیستمیک به خطر شکست سیستم مالی یا شکست کل بازار اطلاق میشود. این ریسک میتواند از بیثباتی یا بحران در مؤسسات مالی نشأت بگیرد و در اثر سرایت به کل نظام مالی انتقال یابد. بهعبارتی ریسک سیستمیک به میزان به همپیوستگی در یک سیستم مالی اشاره دارد جاییکه شکست در یک نهاد مالی میتواند به بحران کل سیستم منجر شود. این تحقیق با توجه به رویکردهای مختلف جهت اندازه‏گیری ریسک سیستمیک به دنبال انتخاب رویکرد بهتر برای اندازه‏گیری ریسک سیستمیک است. انتخاب رویکرد بهتر با توجه به خطای پیش‏بینی ارائه شده توسط هریک از مدل‏ها است. مدلهای به کار گرفته شده اعم از مدل‏های گارچی چند متغیره، مدل ارائه شده توسط برانلس و انگل به نام VCT، مدل‏های عاملی‏، مدل‏های آماری دومتغیره است. نتایج تحقیق نشان می‏دهد که مدل پیشنهادی برانلس و انگل (VCT) خطای کمتری را نسبت به سایر مدل‏ها از خود نشان داده است. Manuscript profile -
Open Access Article
142 - The effect of size and intensity of price jumps on forecasting index volatility in Tehran Stock Exchange
mohsen rajab boloukat ali baghani Ali Najafi Moghadam fatemeh sarraf norouz noorolahzadehIt is very important to distinguish how the volatility in the return of assets occur. For this reason, in recent years, realized volatility and frequencies of daily volatility recognition studies have been developed. This study uses stock prices of 30 big companies of T MoreIt is very important to distinguish how the volatility in the return of assets occur. For this reason, in recent years, realized volatility and frequencies of daily volatility recognition studies have been developed. This study uses stock prices of 30 big companies of Tehran Stock Exchange during the years 1390 (2011) to 1394 (2016) and calculates the realized stock volatility during trading days using the HAR-CJ model to examine the effect of size and intensity of price jumps in predicting index volatility. The results showed that the development of HAR-CJ and HAR-RV-CJ models using the size and intensity of jump did not have a significant effect on improving the index volatility prediction but, to a small extent, the model prediction performance Adjusts for index volatility. Also, using intraday jumps instead of daily jumps, does not improve the performance of the prediction model. Manuscript profile -
Open Access Article
143 - Design and explanation of stock price forecasting model in the real estate companies's stock in the Tehran Stock Exchange using Stochastic Process
hossein ojaghi Zadaleh Fathi Mehrzad MinouieThe present study has designed and explained the stock price forecasting model using stochastic processes. The statistical population of the study is all companies of the mass real estate industry in the Tehran Stock Exchange from 1390 to 1398. Data were analyzed in Evi MoreThe present study has designed and explained the stock price forecasting model using stochastic processes. The statistical population of the study is all companies of the mass real estate industry in the Tehran Stock Exchange from 1390 to 1398. Data were analyzed in Eviews10 and MATLAB software. Predicting stock price behavior and the whole industry index by autoregressive methods and moving average in terms of random processes showed that the explained pattern can not be used to predict stock price behavior but in some random steps, the forecasting error was negligible. Regarding the forecast of stock price behavior, the last three steps of the process, winter have a significant effect on stock price forecast; But the first step has a significant effect on predicting the behavior of the industry index. In the first steps, the error of predicting the behavior of the industry index is very small and the explained model can be used to predict the behavior of the index in the first months of the year. Manuscript profile -
Open Access Article
144 - عنوان مقاله / English Daily Stock Price Movement Prediction Using Sentiment text mining of social network and data mining of Technical indicators
Kamel Ebrahimian ebrahim abbasi Akbar Alam tabriz Amir MohammadzadehThis study predicts the future movement of stock prices in the short term by using the analysis of investors' opinions on the social network. The predictability of stock markets, due to having a complex, dynamic and nonlinear system that it has always been one of the ch MoreThis study predicts the future movement of stock prices in the short term by using the analysis of investors' opinions on the social network. The predictability of stock markets, due to having a complex, dynamic and nonlinear system that it has always been one of the challenges for researchers. In this research, for the first time, we developed a model with 72.08%accuracy for predicting stock movement and predicting the trend by analyzing the feelings of users' opinions and combining it with 20 technical indicators and we use three data mining algorithms include decision tree, Naïve Bayes and Support Vector Machine. According to the results, the support vector machine showed better performance than the other algorithms. It was also found that the next day trading volume and the number of comments have a significant correlation and the results of Granger causality test showed can be used to predict stock price and also it took advantage of the aggregation of users' daily emotions. Manuscript profile -
Open Access Article
145 - Investigating some corporate governance mechanisms and its effect on stock value and projected income in companies listed on the stock exchange
MISAGH AKHOONDI Abdolmajid DehghanTensions between the rights of individuals and organizations have been fundamental problems in societies.Financial markets and powerful corporations are growing dramatically around the world.In the face of this growth, there must be targeted legal and regulatory tools f MoreTensions between the rights of individuals and organizations have been fundamental problems in societies.Financial markets and powerful corporations are growing dramatically around the world.In the face of this growth, there must be targeted legal and regulatory tools for corporate accountability.Corporate governance is designed in the same framework.Corporate governance system is a reaction to the issue of representation and to the separation of ownership from management or, more commonly, the separation of ownership from control of companies, and is itself the result of two main causes;First, each participant has different goals and preferences.Second, each does not have complete information about the other's actions, knowledge, and preferences.Obviously, this separation, assuming effective executive mechanisms of corporate governance, creates the potential for managers to make decisions that are in line with their own interests and the opposite of the interests of shareholders.Gradually, as the authority to exercise direct sovereignty over the owners diminishes, control is transferred to other groups, such as boards and directors.It can be said that any change in the implementation of the governance structure has a great impact on the change of leadership and their performance.The relationship between corporate governance and corporate performance is an important issue in financial matters. Corporate governance aims to strengthen the atmosphere of transparency, honesty and accountability in the management of the organization. Evaluating the performance of corporate governance and examining its mechanisms is very important and has a great impact on economic decisions of companies. Manuscript profile -
Open Access Article
146 - Designing a Model for Measuring the Impact of Intellectual Capital, Profit Quality, Audit Report and Capital Structure on Bankruptcy Risk of Tehran Stock Exchange Companies
Narjes Mogharebi Ali Asghar Anvary Rostamy Roya Darabi hamidreza vakilifardThe purpose of this study is to design a model to investigate the impact of variables of intellectual capital, profit quality, nature of audit report and capital structure on the risk of bankruptcy of Tehran Stock Exchange companies. The present study is an applied, ana MoreThe purpose of this study is to design a model to investigate the impact of variables of intellectual capital, profit quality, nature of audit report and capital structure on the risk of bankruptcy of Tehran Stock Exchange companies. The present study is an applied, analytical-mathematical research. Its spatial territory is Tehran Stock Exchange and its temporal territory is from 1391 to 1397. In this study, regression test method has been used to predict bankruptcy. Findings show that intellectual capital of 0.212 of changes in bankruptcy risk forecasting, profit quality of about 0.207 of changes of bankruptcy risk forecasting, nature of audit report 0.194 of changes of bankruptcy risk forecasting, and structure Capital 0.362 predicts changes in corporate bankruptcy risk. Manuscript profile -
Open Access Article
147 - A comparative study between the effectiveness of ARIMA and ARFIMA models in predicting the interest rate and the treasury exchange rate in Iran
mohadeseh razaghi hashem nikomaram Alireza Heidarzadeh Hanzaei farhad ghaffari Mahdi Madanchi ZajDue to the importance of predicting economic variables, different models have been created to predict the future values of variables. In fact, economic models can be tested by checking the level of forecasting accuracy. The main purpose of this study is prediction of Ir MoreDue to the importance of predicting economic variables, different models have been created to predict the future values of variables. In fact, economic models can be tested by checking the level of forecasting accuracy. The main purpose of this study is prediction of Iran interbank offered rate and Iran treasury exchange rate as interest rates indicators for facilitating interest rate risk management. Two econometric models including ARFIMA and ARIMA have been used for forecasting. Thus, the ARFIMA model considering long-term memory and the ARIMA model without considering long-term memory have been considered. The evaluation of the prediction accuracy of the two models using the monthly Iran interbank offered rates data and also the monthly Iran treasury exchange rates data shows that both the interbank offered rates data and the Islamic treasury bond rates data, ARIMA model has a better performance compared to ARFIMA model in predicting data. Manuscript profile -
Open Access Article
148 - نقش واسطه ای پیشبینیپذیری و مقایسهپذیری سود در تأثیر مولفه حاکمیتی گزارشگری عملکرد پایدار بر ریسک سقوط قیمت سهام و نقدشوندگی سهام
Morteza Pahlavan Ali Asghar Anvary Rostamy Roya Darabiبا توجه به اهمیتی که سرمایهگذاران برای بازده سهام خود قائل هستند، پدیده سقوط سهام منجر به کاهش شدید بازده میشود. بسیاری از پژوهشگران معتقدند تغییرات قیمت سهام شرکت از مدیریت اطلاعات داخلی آن نشأت میگیرد. از آنجایی که قیمت سهام، نه تنها از طریق اطلاعات مالی بلکه از طر Moreبا توجه به اهمیتی که سرمایهگذاران برای بازده سهام خود قائل هستند، پدیده سقوط سهام منجر به کاهش شدید بازده میشود. بسیاری از پژوهشگران معتقدند تغییرات قیمت سهام شرکت از مدیریت اطلاعات داخلی آن نشأت میگیرد. از آنجایی که قیمت سهام، نه تنها از طریق اطلاعات مالی بلکه از طریق اطلاعات اجتماعی، حاکمیتی، اقتصادی و زیست محیطی نیز دستخوش تغییر می شود، از این رو انتشار یک گزارش خاص نظیر بعد حاکمیتی گزارشگری عملکرد پایدار میتواند بر نقدشوندگی سهام و ریسک سقوط قیمت سهام اثر گذار باشد. پژوهش حاضر با استفاده از رویکرد مدل-سازی معادلات ساختاری به دنبال پیشبینی معیارهای ریسک سقوط قیمت سهام و نقدشوندگی آن از طریق گزارشگری پایداری حاکمیتی و معیارهای دقت پیشبینی و قابلیت مقایسه سود (معیارهای داخلی) است. بدین منظور و با استفاده از روش حذف سیستماتیک، 147 شرکت پذیرفته شده در بورس اوراق بهادار تهران برای بازه زمانی 1391 تا 1400 به عنوان نمونه انتخاب شدند. جهت تجزیه و تحلیل دادهها از نرم افزار PLS استفاده گردید. نتایج پژوهش نشان داد که مولفه حاکمیتی گزارشگری عملکرد پایدار منجر به افزایش قابلیت مقایسه سود، افزایش نقدشوندگی سهام و کاهش ریسک سقوط آتی قیمت سهام میگردد. دیگر یافتهها نشان داد که قابلیت مقایسه سود بر رابطه میان گزارشگری عملکرد پایدار حاکمیتی با ریسک سقوط آتی قیمت و نقدشوندگی سهام نقش واسطهای دارد. این در حالی است که دقت پیش بینی سود بر ریسک سقوط آتی قیمت سهام و نقدشوندگی سهام تاثیر معناداری ندارد. Manuscript profile -
Open Access Article
149 - Developing a model for predicting the Tehran Stock Exchange index using a combination of artificial neural network and Markov hidden model
Leila Talaie Kakolaki Mehdi Madanchi Taghi Torabi Farhad GhaffariThe purpose of this study was to design a new model for predicting the Tehran Stock Exchange index using pattern recognition in a combination of hidden Markov model and artificial intelligence. The present study is an applied type and mathematical analytical method. Its MoreThe purpose of this study was to design a new model for predicting the Tehran Stock Exchange index using pattern recognition in a combination of hidden Markov model and artificial intelligence. The present study is an applied type and mathematical analytical method. Its location is the Tehran Stock Exchange and during the years 2010 to 2020. Findings showed that the prediction error rate with artificial neural network has a higher accuracy than Markov's hidden model. Also, the prediction error of the hybrid model is much lower than the other two models for predicting the total stock index of Tehran Stock Exchange, so it has higher accuracy for forecasting stocks. According to the MAPE index, the hybrid model method could improve the predictive power of the artificial neural network by 0.044% and also improve the predictive power of the hidden Markov model by 0.70%. Manuscript profile -
Open Access Article
150 - Predicting Network linkages of banking system distress based on operational risks and behavioral finance components
ahmad bidi Fraydoon Rahnamay Roodposhti Gholam Reza Gholami Jamkarani HAMIDREZA KORDLOUIE Mortaza Baky HasueeThe present research is aimed at prediction of network linkages of banking system distress based on operational risks and behavioral finance approach. Methodology of the present research is of survey descriptive, practical from the purpose standpoint. Notably, in order MoreThe present research is aimed at prediction of network linkages of banking system distress based on operational risks and behavioral finance approach. Methodology of the present research is of survey descriptive, practical from the purpose standpoint. Notably, in order to reach this purpose, firstly, based on study and review of theoretical basics, research variables were introduced. Then, by making use of Krejcie and Morgan Table, 384 participants were selected, and upon distribution of questionnaire among the aforesaid, research data were collected. Furthermore, in order for analysis of data and estimation of research empirical models, the researcher used structural equation modeling (SEM) and Smart PLS software. Of note, findings of this research indicate that behavioral financial standpoints and operational risk have significant effects on prediction of banking network disorder. Furthermore, based on estimated beta coefficients, among behavioral financial elements, economic behavior, cognitive standpoint, judgment biases, heuristic behaviors, decision making biases and value and return of stocks have respectively the highest effect on banking disorder, and among operational risk elements, human resources risk, systemic risk, transaction risk, technology risk and fraudulent and deception risk have respectively the highest effect on banking disorder. Manuscript profile -
Open Access Article
151 - Proposing a novel model based on ARIMA technique for forecasting housing price: a case study of Tehran
Hosseyn Mombeyni Morteza Hashempoor Shahla RoshandelDetermination and prediction of housing price in urban areas plays a significant role for governments, public and private enterprises, and financial evaluators. An accurate estimation of the housing price can be employed for future planning and decision making in many u MoreDetermination and prediction of housing price in urban areas plays a significant role for governments, public and private enterprises, and financial evaluators. An accurate estimation of the housing price can be employed for future planning and decision making in many urban and regional policies. However, the growth of the housing sector has a profound impact on gross national product, resulting in a significant increase in employment. On the other hand, an increase in loan for purchasing house leads to a rise in liquidity and inflation rate. This means that the gap between the income and housing price is increased. Therefore, it is necessary to develop new models for making decisions in order to prevent the increase in the inflation rate and housing price. According to the key importance of housing price, a number of models have been developed to formulate the price behavior with regard to its effective components. In this study, a novel model based on the ARIMA method for forecasting and formulating the housing price has been developed. The results show that the model proposed has a high potential (with a determination coefficient of 99.7%) to foresee the housing prices in the city of Tehran. Manuscript profile -
Open Access Article
152 - Testing investment strategies based on behavioral finance
Hashem Nikoomaram Ali Saeedi Kiarash MehraniThis study has tested momentum and reverse investment strategies in a behavioral finance framework, based on various optimistic, pessimistic and normal market sentiments. At the first step, sentiment Index by means of ARMS Adjusted Trading Index was measured. Then, maki MoreThis study has tested momentum and reverse investment strategies in a behavioral finance framework, based on various optimistic, pessimistic and normal market sentiments. At the first step, sentiment Index by means of ARMS Adjusted Trading Index was measured. Then, making use of portfolio analysis, we formed portfolios for 1 month and 3 month periods based on momentum and reverse strategies. Portfolios classification was done based on volatility factor in various behavioral periods. Then returns of different portfolios and strategies was tested by a probit model in different market sentiments (i.e. optimism, pessimism and normal) Finding of the study reveal that in a normal market sentiment, most of behavioral finance strategies has been successful in terms of return. Moreover, reverse strategies have shown higher efficiency in a normal market state, compared to a momentum strategies. It was surprising when we found that both in a pessimistic and optimistic period, not only any excess return was experienced, but also mostly lead to loss. In short term, momentum portfolios produced higher return than reverse ones. Unit root test proved stationary of the sentiment. Since the market was found to be non-stochastic, we conclude stock market inefficiency. We found in a VAR model framework that optimism is a one-way Granger Couse of stock return, furthermore stock return is a one-way Granger Couse of pessimism. Manuscript profile -
Open Access Article
153 - Designing a Hybrid Intelligent Model for Prediction of Stock Price Golden Points
Mohammad Moshari Hosein Didehkhani Kaveh Khalili Dameghani Ebrahim AbbasiThe purpose of this research is to provide an intelligent model for prediction of golden points on stock price chart as a decision support system. For conduction of this research, the data of the automotive and parts manufacturing industry during 2001 through to 2016 we MoreThe purpose of this research is to provide an intelligent model for prediction of golden points on stock price chart as a decision support system. For conduction of this research, the data of the automotive and parts manufacturing industry during 2001 through to 2016 were used. First, the obtained results from application of different forecasting models based on data mining were compared with each other. Next, the research variables were optimized by genetic algorithm and remodeling took place. The results indicated that the golden points could be predicted with reasonable accuracy and optimization did not enhanced accuracy in all these models, yet it significantly reduced gross error. Manuscript profile -
Open Access Article
154 - predicted profit on the possibility of revision in profit prediction
Majid Zanjirdar Saeid GhasemiPrediction of management is a key mechanism of voluntary disclosure. Previous studies in this area have shown evidences that managers disseminate the profit predictions to provide more information and guidance to the market and the market significantly react to it.After MorePrediction of management is a key mechanism of voluntary disclosure. Previous studies in this area have shown evidences that managers disseminate the profit predictions to provide more information and guidance to the market and the market significantly react to it.After designing the mentioned indices, the data of transactions conducted in the study five-year duration i.e. 1390-94 (2011-15) has been collected from the Stock Exchange. The statistical sample is consisted of 107 companies that have been selected using systematic elimination method that totally were 535 year-firm. In this study to assess the hypotheses, the linear regression and correlation have been used. In order to data analysis and test the hypotheses, the EVIEWS software is used. What can be considered in total summing up and conclusion of the study hypotheses is that the buy and hold returns, the number of revision and the seasonal error in predicted profit have an impact on the possibility of revision in profit prediction. In addition, decision-making based on informed transactions by insiders has an impact on the relationship between the mentioned variables. Manuscript profile -
Open Access Article
155 - Efficiency compared to ARIMA and ARFIMA models for modeling and prediction of Tehran Price Index (TEPIX)
Habibollah salarzehi Mansoor kasha kasha Seyed-Hasan Hosseini Mohammad DonyaeiThis article examines the forecast performance of ARFIMA and ARIMA models using data on daily stock price index of Tehran in period 25/11/2001 to 30/11/2011. To estimate the d parameter and other parameters, the NLS method in the software package Oxmetric / pcgive was u MoreThis article examines the forecast performance of ARFIMA and ARIMA models using data on daily stock price index of Tehran in period 25/11/2001 to 30/11/2011. To estimate the d parameter and other parameters, the NLS method in the software package Oxmetric / pcgive was used. After comparing the results of research models, ARFIMA models based on AIC, the model was found superior in modeling TEPIX. Also we use naive methods for estimating the prediction. Comparing the accuracy of the prediction models by criteria such as MAPFE and RMSFE and confidence intervals of the real values, we can deduce that the first Performance difference between the predicted long-term memory ARFIMA model is very minor compared to the ARIMA model And Secondly, inefficient ARFIMA model in Tehran capital market forecast is quite evident. Manuscript profile -
Open Access Article
156 - Comparing the performance Of Artificial Neural Networks(ANN) and Auto Regressive Moving Average(ARIMA) Model in Modeling and Forecasting Short-term Exchange Rate Trend in Iran
Abbas Ali Abunoori Fardad Farokhi Seyedeh Fatemeh ShojaeyanExchange rate and its related fluctuation plays a significant role as one of the most important issues of each country's foreign trade sector. Many factors such as economic, politics, and psychological factors impress on exchange rates and these factors create more unce MoreExchange rate and its related fluctuation plays a significant role as one of the most important issues of each country's foreign trade sector. Many factors such as economic, politics, and psychological factors impress on exchange rates and these factors create more uncertainty situations. Policymakers’ attempt is to reduce this uncertainty via forecasting this variable with minimal error.Artificial neural networks have high potential in modeling complex processes and forecasting dynamic nonlinear paths .Therefore, in this study has tried to use the artificial neural network (ANN) In addition to modeling and forecasting daily exchange rates during the period of March 2002 to March 2005, and minimizing the forecast error by this method, its results were compared with that of ARIMA based on forecasting accuracy evaluation criteria , and to examine the sensitivity of model results toward exchange rates.Estimation of the model with the same method for three data sets exchange rate including dollar,euro and pound have been performed .Results indicate that used neural network has better predictive power in comparison with arima model while pound and Euro exchange rates’ prices are function of their yesterday prices and dollar exchange rate price is a function of its price over the past 6 days . Manuscript profile -
Open Access Article
157 - Evaluate the Ability of Social Networks to Predict the Direction and Stock Prices in Tehran Stock Exchange
Reza Raie Seyed Farhang Hoseini Maedeh Kiani HarcheganiExamining the ability and efficiency of social network on price and direction of stock price is important, because of social network boom. In this research, we observe the herding behavior based on buy and sell offer in one of the Iranian social network (sahamyab.com) u MoreExamining the ability and efficiency of social network on price and direction of stock price is important, because of social network boom. In this research, we observe the herding behavior based on buy and sell offer in one of the Iranian social network (sahamyab.com) using neural network. The duration of research between July 2013to June 2014(1year) and based on TSE is divided to period of bull and bear market. The sample is selected on two hypotheses, ten symbols from active stocks listed by TSE and another ten symbol from most viewed and active on social network. This research done on two parts: direction forecast and price forecast. Historical price and buy/sell offer in social network with 3 to 10 lags used. Feed forward neural network (FFNN) with 3 to 10 data lags and 1 hidden layer and up to twenty neuron used to find optimal network and used to forecast. In price forecast, there is no significant difference, But in directional of stock price forecast, we found that it's significant for most viewed share in bull market and for active share in bear market. Manuscript profile -
Open Access Article
158 - Evaluation Fundamental based risk model in predicting stock prices
Ehsan kamali Seyyed Abbas Hashemi Dariush ForoughiHow to measure the risks is one of the most challenging issues in the stock valuation models. This study is designed based on a new methodology for risk measurement in valuation models based on fundamental factors related. Therefore beta of excess equity returns and bet MoreHow to measure the risks is one of the most challenging issues in the stock valuation models. This study is designed based on a new methodology for risk measurement in valuation models based on fundamental factors related. Therefore beta of excess equity returns and betas of size and book-to-market based on earnings, as the risk adjustment was combined to the present value based on risk-free rate in valuating model. Evaluation process was conducted in two stages, first during the period 2002 to 2011 using short time-series regressions, risk-adjustment coefficients were calculated at three levels: firm, industry and selected portfolios and the coefficients in the second stage along with other required data in the research model used to predict the stock price for the year 2012. The results show good performance of applying the model to predict the stock price of listed companies in Tehran Stock Exchange. Manuscript profile -
Open Access Article
159 - Style Investing and Return Predictability
Maryam Davallou Hamidreza FartokzadehThis research investigates cross section individual stock return predictability by style return in Tehran Stock Exchange. Test of stock return predictability is performed based on Fama and Mac-Beth regression model using data from 1380 to 1389. Also for profound analysi MoreThis research investigates cross section individual stock return predictability by style return in Tehran Stock Exchange. Test of stock return predictability is performed based on Fama and Mac-Beth regression model using data from 1380 to 1389. Also for profound analysis, the relation between co-movement of stock return with its style return and momentum is examined. So, Portfolio analysis approach based on dual sorting is used for the latter test. The outcomes of this research confirm future cross-section stock return predictability by style-based return over twelve month formation period. The results indicate that co-movement of stock return with its style return generates variation in momentum profit. This finding is restricted to twelve month formation period and one month future return horizon and is not observed over longer horizon future return. Manuscript profile -
Open Access Article
160 - An Optimization of Moving Average Stock Price in Tehran Stock Exchange: Meta-heuristic approach Adaptive Improved Genetic Algorithm
Mahboobeh Asghartabar ledari Ahmad Jafari SamimiPredict the stock price is an important topic in financial markets. Is commonly use of technical tools in this area and one of them most functional, are moving averages. The use of two moving averages, the most common method to predict trends, which is in need of two pe MorePredict the stock price is an important topic in financial markets. Is commonly use of technical tools in this area and one of them most functional, are moving averages. The use of two moving averages, the most common method to predict trends, which is in need of two periods. The optimal lengths for both short-term and long-term period for each stock, according to a recent trend, they are different. Find the optimal lengths with traditional methods of costly and often do not reach the global optimal answer. The perfect solution are using of smart tools such as genetic algorithms. Genetic algorithm have been used in this study, is Adaptive Improved Genetic Algorithm that much faster finds a global optimal answer. In this study, data's of the selected companies in diverse industries in Tehran Stock Exchange from April 2011 to March 2016 have been evaluated. The results show, when the algorithm reaches the optimal time period, which its parameters are correctly set. Manuscript profile -
Open Access Article
161 - Financial management and Dungeon Kruger's (self-help)
Behzad Pahleh Seyed Mozaffar Mirbargkar Abolfazl ZolghadrThe Dunning-Kruger effect is a kind of cognitive bias in unprofessional people who suffer from the illusion of superiority and incorrectly evaluate their ability to be overly real. This bias is attributed to the metacognitive inability of unprofessional individuals to i MoreThe Dunning-Kruger effect is a kind of cognitive bias in unprofessional people who suffer from the illusion of superiority and incorrectly evaluate their ability to be overly real. This bias is attributed to the metacognitive inability of unprofessional individuals to identify their disability and is a blood stream in the human body. Financial managers also suffer from this cognitive error in their own assessment of others, as financial managers with a level of ability and experience usually evaluate themselves more often than they are. For example, those who have the capability of an accounting expert have their own accounting officer and those who have the ability to become accounting officer, they identify themselves as financial advisors and those who are capable of a financial manager, as financial advisers, and usually themselves more than what they are. Or vice versa, they are less than what they are, which is due to self-esteem or self-righteousness, or to Duning Kruger's. In this research, we examine the characteristics and general criteria of financial managers and identify the skills of financial managers, and the results show that the skills of financial managers are usually more than what they have in them. Manuscript profile -
Open Access Article
162 - Investigation the Effects of management earning forecasts on the cost of equity capital
Azita Jahanshad Mohsen ZardkouhiThe main object of this study is investigation of effectiveness state of earning forecasts news on the firms cost of equity capital and look for answer to this question that is the cost of equity capital affected importantly by forecasts negative or positive adjustment MoreThe main object of this study is investigation of effectiveness state of earning forecasts news on the firms cost of equity capital and look for answer to this question that is the cost of equity capital affected importantly by forecasts negative or positive adjustment news or not? at this course tried to more over than separated effects of forecasts positive adjustment news or negative adjustment news on the cost of equity capital, investigate the symmetrical or asymmetrical effects of these two types of news on the cost of equity capital. for this purpose four hypothesis compiled and examined with use of gathered data from statistical samples include 132 firms at time period from 1385 to 1389by put panel and compound data regression method into operation Resulted Experimental evidences from this research indicated that both forecasts negative and positive adjustment news affected the firms cost of equity capital in the manner that negative adjustment news have increasing effect and positive adjustment news have decreasing effect on the cost of equity capital. The results also indicated that effect measure of negative adjustment news on the cost of equity capital have been more than positive adjustment news. In addition the investigations indicated that for descending profitability trends, management’s preemption in issue of earning forecasts negative adjustment news was modifying the really earning declare effect on the cost of equity capital. Manuscript profile -
Open Access Article
163 - Forecasting Tehran’s bourse price index using return-based fuzzy time series
Farid Radmehr Naser Shams GharnehDuring the recent years extensive researches have been done on fuzzy time series. In many of these studies, universe of discourse and relevant intervals have been determined based on levels of price or data; in this study a new type of universe of discourse is establish MoreDuring the recent years extensive researches have been done on fuzzy time series. In many of these studies, universe of discourse and relevant intervals have been determined based on levels of price or data; in this study a new type of universe of discourse is established based on rate of return concept in financial markets. Another point that has a significant effect on the performance of fuzzy time series models is the length of intervals, therefore doing research in this area became an interesting topic for time series researchers, there are some studies on this issue but their results are not good enough. So we propose a novel simulated annealing heuristic algorithm that is used to promote the accuracy of forecasting. The experimental results show that proposed model (RBFTS) is more accurate than existing models on forecasting Alabama university enrollments data. At the final step, Tehran’s bourse price index (TEPIX) is used as a case study for forecasting. The obtained results indicate a good forecasting performance on this test problem. Manuscript profile -
Open Access Article
164 - Survey of the effects fundamental variables on stock price
Farhad Hanifi Mirfeyz Fallah Shams Leyla AbolfazliForecasting stock price and adopting proper strategy for stocks dealing are subject to many research works. Fundamental analysis is one of the interesting points in this regard. The present work surveys to what extent the fundamental variables represents the stock statu MoreForecasting stock price and adopting proper strategy for stocks dealing are subject to many research works. Fundamental analysis is one of the interesting points in this regard. The present work surveys to what extent the fundamental variables represents the stock status. The period under study was from 2006 to 2010 and 51 companies in the stock market were under consideration. The data were studied on the weekly and monthly bases. Panel data method was used to study the relation between the variables in the study. Except for stockholder rights turnover, the results showed a positive significant relation between the fundamental variables under consideration including profit per share, predicted profit per share, and book value on one hand and stock price on the other hand. That is, the majority of the variables represent price of stocks for more than 90%. Moreover, the regression model obtained from the annual fundamental variables illustrated higher representation power comparing with seasonal data, which shows merits of longer-term perspective. Manuscript profile -
Open Access Article
165 - The Relationship of Management Optimism and Earnings Smoothing between Banks Listed in Tehran Stock Exchange and OTC
Jamal Bahri SalesToday managers to attract investors try to show revenue and income in maximum level as one of the criteria for their performance. They may be smooth the reported incomes by selecting specific accounting policies, accounting estimates and accruals management. Therefore, MoreToday managers to attract investors try to show revenue and income in maximum level as one of the criteria for their performance. They may be smooth the reported incomes by selecting specific accounting policies, accounting estimates and accruals management. Therefore, reported earnings may be differing from result of actual performance. The purpose of this study was to investigate the relationship of management optimism and earnings smoothing between banks listed in Tehran stock exchange and OTC during 2010 to 2014. Adjusted community consists of 65 year-banks. To answer the research question two hypotheses through ordinary least square regression and binary logistic in form of multivariate liner by using Pooled data were tested. The results show that the optimism managers in compare with others, more likely to report earnings smoothed by accruals and IKLE smoothing index. The results also indicate that, larger and older banks are more likely to report earnings smoothed by accruals and IKLE smoothing index. The findings indicate that, the banks that have a high market to book value, less likely to smooth earnings by IKLE model. Manuscript profile -
Open Access Article
166 - The effect of surplus free cash flow, corporate governance and firm size on earnings predictability
Fatemeh Ghorbani M. Hamed KhanmohammadiThe aim of this paper is investigates the impact of surplus free cash flow, corporate governance and firm size on earnings predictability firms in the Tehran Stock Exchange. Free cash flow surplus and earn as independent variables. Also corporate governance mechanisms ( MoreThe aim of this paper is investigates the impact of surplus free cash flow, corporate governance and firm size on earnings predictability firms in the Tehran Stock Exchange. Free cash flow surplus and earn as independent variables. Also corporate governance mechanisms (independent board of directors, independent chairman, institutional ownership, and managerial ownership) and firm size as moderator variables. The final sample using of 100 firms listed in the Tehran Stock Exchange between2008 to 2014 research done. Linear regression analysis is used for testing the hypotheses. Free cash flow surplus and earn as independent variables. Also corporate governance mechanisms (independent board of directors, independent chairman, institutional ownership, and managerial ownership) and firm size as moderator variables. Result of the test hypotheses indicates that the excess free cash flow and Earnings predictability have effect.and there is also corporate governance mechanisms (independent board of directors, independent chairman, institutional ownership, and managerial ownership) on the relationship between excess free cash flow and Earnings predictability have no effect. Manuscript profile -
Open Access Article
167 - Discuss Optimal Portfolio Efficiency in terms of Kurtosis Model in Phase environment
Ehsan Ghadrdan Khosro Faghani Makrani Samira SolgiThe most important problem for investors, at the beginning stages of their works, is the way of assigning their investment to one or more different investment alternatives in such a way that with the least possible risk the maximum return become obtainable. In the econo MoreThe most important problem for investors, at the beginning stages of their works, is the way of assigning their investment to one or more different investment alternatives in such a way that with the least possible risk the maximum return become obtainable. In the economic literature this is known as the problem of portfolio selection. In present research, portfolio classic performance efficiency (Markowitz variance average model) was discussed in phase environment based on Kurtosis as target function. The research method Used in this study is post event semi empirical design. In this research, one discussed 195 monthly portfolios in 10 years (2007-2016) in companies accepted in Tehran stock exchange and risk and yield of portfolio was estimated in phase and classic environment. In another step, significant difference between risk and yield was predicated and the results showed that risk and yield have significant difference in phase environment based on kurtosis model. Manuscript profile -
Open Access Article
168 - Application of Geometric Brownian motion in prediction of gold price and currency rate
Hojjatollah Sadeqi Mohammadesmaeil Fadaeinejad Alireza VarzidehVariables such as exchange rates and gold prices has a great importance for economic actors therefore the aim of this study were determined as prediction of U.S Dollar exchange rate and gold coin price in Iran Market. Forecasting has been done by Geometric Brownian Moti MoreVariables such as exchange rates and gold prices has a great importance for economic actors therefore the aim of this study were determined as prediction of U.S Dollar exchange rate and gold coin price in Iran Market. Forecasting has been done by Geometric Brownian Motion model that is considered as one of the stochastic differential equations. Data were collected and analyzed in the period from the beginning of 1392 until the end of 1395. also forecasting prices for each under study time series has been done in various forecasting horizons involved 7, 14, 21, 30, 60, 90, 180 and 360 day time period. The results show that Geometric Brownian Motion model can simulate the prices of gold coin and exchange rate highly accurate in accordance with the criteria of mean absolute percentage error. Also The other results obtained from this study is that According to ten different prediction accuracy criteria, By increasing the forecast horizon, ability of the GBM model in simulation and forecasting exchange rates and the price of gold coin decreases. Manuscript profile -
Open Access Article
169 - The effect of corporate governance mechanisms on the relationship between excess free cash flow and earnings forecast
Ebrahim AbbasiThe aim this paper is investigates the impact of corporate governance mechanisms on the relationship between excess free cash flow and earnings predictability. Earnings forecasts using regression relationship between of one-year-ahead operating cash flow and curre MoreThe aim this paper is investigates the impact of corporate governance mechanisms on the relationship between excess free cash flow and earnings predictability. Earnings forecasts using regression relationship between of one-year-ahead operating cash flow and current earningsachieved. Free cash flow surplus and corporate governance mechanisms (the ratio of independent directors, the Board of Directors, the duality of the role of the Director, the percentage of shares owned by institutional investors and management ownership of shares) as independent variables.Using a sample of 102 firms listed in the Tehran Stock Exchange between2010 to 2014 research done. To estimate the model, multiple linear regression model is used in the the cumulative data. The final result of the test hypotheses indicates that the excess free cash flow and Earnings forecasts and there is also corporate governance mechanisms (the ratio of independent directors, the Board of Directors, the duality of the role of Director, the percentage of shares owned by institutional investors and ownership of shares management) on the relationship between excess free cash flow and Earnings forecasts have no effect. Manuscript profile -
Open Access Article
170 - Investigate the relationship between investor sentiment, courage in predicting dividends and future corporate performance
Reza Gholami Jamkarani Zahra Akbari Masoud BakhtiariThe purpose of this research is to investigate the relationship between investor sentiment, courage in predicting dividends and future performance of the company in Tehran Stock Exchange. The research is applied from the direction of the target, and, depending on the ty MoreThe purpose of this research is to investigate the relationship between investor sentiment, courage in predicting dividends and future performance of the company in Tehran Stock Exchange. The research is applied from the direction of the target, and, depending on the type of research project, relying on historical information, then the event. The method of research inference is inductive and correlation type and consists of 3 hypotheses. The research community is the accepted companies in Tehran Stock Exchange for a period of 5 years. To document the results of statistical analysis and provide final solutions, the researcher used a statistical method using Eviews software to analyze the questions and hypotheses. The research was conducted using regression Compound linear and F and t tests. The results of the test of research hypotheses showed that investor's feelings on courage affect the prediction of dividends and company growth, but not affect future returns. Manuscript profile -
Open Access Article
171 - Predicting bankruptcy of companies listed on the Stock Exchange using the artificial neural network
Mohsen Vaez-Ghasemi Saeid Ramezanpour ChardehBeing informed of capital market’s companies financial situation is one of the shareholders and economic analysts’ perturbation. Thus, financial market analysts and researchers were looking for methods to predict capital market’s company’s future MoreBeing informed of capital market’s companies financial situation is one of the shareholders and economic analysts’ perturbation. Thus, financial market analysts and researchers were looking for methods to predict capital market’s company’s future conditions. This research is finding a model to predict bankruptcy of stock exchanges market’s companies with using the artificial neural network. In this research we used Zemijewski financial ratios with one macro – economic variable to predict companies’ bankruptcy. Population of study was selected from the accepted companies in Iran’s stock and exchanges organization. Financial ratios have been extracted from companies’ financial statement in a five years’ period between 2010 and 2014, finally we choose 84 companies that divided to salubrious and bankrupt equal number in each. We used multi-layer perceptron (MLP) with back propagation algorithm to create predictor model and data analysis. The network has been trained once with financial ratios and again with additional macro – economic variable to confirm that the accuracy of network model will increase by additional macro – economic variable. Ultimately the designed model in total mode has 92.95 percent of accuracy and 85 percent correct prediction of bankrupted companies for one year earlier of bankruptcy. Manuscript profile -
Open Access Article
172 - Financial Astrology in Stock Market Analysis
Mohsen Ghasemian Feraydoon Rahnamay RoodposhtiFinancial Astrology as a tool in field of Technical Analysis is used in stock market analysis for many years. Although it's an old science and a known way for market analysts but in Iran it's unknown for traders and academic researchers. A doubt in point of view is nece MoreFinancial Astrology as a tool in field of Technical Analysis is used in stock market analysis for many years. Although it's an old science and a known way for market analysts but in Iran it's unknown for traders and academic researchers. A doubt in point of view is necessary for investigators to test the claims but mysterious tools and unknown references would make it slow in science development and use it by market technicians. In this research some references in financial astrology including books, articles and related soft ware would be introduced to know the position of this field in financial markets. Results of this research show the usage of Financial Astrology in Capital Market Analysis and would help us to have a better realization of trading cycles and finally can help in portfolio stock selection. Manuscript profile -
Open Access Article
173 - The Impact of Agency Costs on Predicting Profitability
M. B. Mohhamadzadeh MoghadamToday's review of the articles shows that the agency cost has been one of the most important fields of studying in accounting.Therefore, the main objective of this study is to evaluate the effect of agency costs on predicting profitability in Tehran Stock Exchange. In t MoreToday's review of the articles shows that the agency cost has been one of the most important fields of studying in accounting.Therefore, the main objective of this study is to evaluate the effect of agency costs on predicting profitability in Tehran Stock Exchange. In this research, the benchmark for agency cost includes earninig management, capital structure, corporate governance mechanism and asset turnover ratio.Regression analysis is used to examine hypotheses of the study. The data set includes 105 companies accepted in Tehran Stock Exchange for the period of2010 to 2016. The results of the hypothesis of this research show that among the criteria for measuring the agency cost, there is a positive and meaningful relationship between institutional ownership and asset turnover ratio with predicting profitability.These findings also showed that there is no significant relationship between capital structure and predicting profitability. Additionally, the relationship between earnings management and predicting profitabilityis meaningfulandnegative.The main reason for this negativerelationship can be the moral hazard resulting from the information asymmetry of earnings management. Manuscript profile -
Open Access Article
174 - Day-ahead stock price forecasting using hybrid model
Vahid Vafaei Ghaeini Alimohammad KimiagariForecasting financial markets is an important issue in finance area and research studies. Importance of forecasting on one hand and its complexity, on the other hand, researchers have done much work in this area and proposed many methods. In this research, we propose a MoreForecasting financial markets is an important issue in finance area and research studies. Importance of forecasting on one hand and its complexity, on the other hand, researchers have done much work in this area and proposed many methods. In this research, we propose a hybrid model include wavelet transform, ARMA-EGARCH and NN for day-ahead forecasting of stock market price in different markets. At first WT is used to decompose and reconstruct time series into detailed and approximated parts. And then we used ARMA-EGARCH and NN models respectively for forecasting details and approximate series. In this model we used technical index by approximate part to the improvement of our NN model. Finally, we combine prediction of each model together. For validation, proposed model compare with ANN, ARIMA-GARCH and ARIMA-ANN models for forecasting stocks price in UA and Iran markets. Our results indicate that proposed model has better performance than others model in both markets. Manuscript profile -
Open Access Article
175 - پیش بینی الگو برای واحدهای تصمیم گیرنده در تحلیل پوششی داده ها
مرتضی شفیعی فرهاد حسین زاده لطفی هیلدا صالحاگرچه تحلیل پوششی داده­ها یک ابراز قدرتمند برای ارزیابی عملکرد واحدهای تحت ارزیابی می­باشد ولی این تکنیک دارای محدودیت­هایی نیز می­باشد. به عنوان نمونه یکی از محدودیت­های این روش، ارزیابی عملکرد سیستم براساس ورودی و خروجی­های قدیم است بنابر Moreاگرچه تحلیل پوششی داده­ها یک ابراز قدرتمند برای ارزیابی عملکرد واحدهای تحت ارزیابی می­باشد ولی این تکنیک دارای محدودیت­هایی نیز می­باشد. به عنوان نمونه یکی از محدودیت­های این روش، ارزیابی عملکرد سیستم براساس ورودی و خروجی­های قدیم است بنابراین نتایج ارزیابی به­دست آمده از مدل­های کلاسیک DEA، برای پیش بینی تغییرات کارایی واحدها در آینده و در نتیجه ارایه الگوی مناسب برای رسیدن به یک واحد کارا، کاربردی نمی­باشد . بنابراین هدف این مقاله پیشنهاد یک روش جدید به منظور پیش بینی کارایی سیستم براساس ورودی و خروجی شبیه سازی شده با استفاده از سیستم پویا و تکنیک­های شبیه سازی است. زیرا با پیش بینی کارایی واحد تحت ارزیابی، مدیران در یک سیستم می­توانند برنامه ریزی دقیق­تری برای آینده داشته باشند. برای این منظور با استفاده از یک حلقه بازخورد، ورودی­ها و خروجی­ها در واحدهای تصمیم گیرنده در آینده مورد پیش بینی قرار گرفت سپس با استفاده از مدل CCR و ورودی­ها و خروجی­های پیش­بینی، شده به پیش بینی کارایی واحد تحت ارزیابی پرداختیم. Manuscript profile -
Open Access Article
176 - پیش بینی خطر سکته مغزی بر اساس علائم کلینیکی با استفاده از روش رگرسیون لجستیک
مائده غلام آزاد جعفر پورمحمود علیرضا آتشی مهدی فرهودی رضا دلجوان انوریمدل سازی ریاضی یکی از روش های عملی است که می توان از آن برای حل مسائل واقعی استفاده کرد. مدلسازی را میتوان با استفاده از روشهای مختلفی از جمله روشهای آماری که میتوان از آنها برای پیشبینی رویدادهای مختلف استفاده کرد، انجام داد. سلامت یکی از مهمترین زمینه های تحقیقا Moreمدل سازی ریاضی یکی از روش های عملی است که می توان از آن برای حل مسائل واقعی استفاده کرد. مدلسازی را میتوان با استفاده از روشهای مختلفی از جمله روشهای آماری که میتوان از آنها برای پیشبینی رویدادهای مختلف استفاده کرد، انجام داد. سلامت یکی از مهمترین زمینه های تحقیقاتی در جهان امروز است. از بین بیماری های مختلف در بخش سلامت، این مطالعه مربوط به سکته مغزی است که دومین عامل مرگ و میر و ناتوانی طولانی مدت انسان است که منجر به انجام این تحقیق شده است. هدف اصلی این تحقیق طراحی و ساخت یک مدل پیشبینیکننده سکته مغزی بر اساس علائم و گزارشهای بالینی بیماران است که پیش بینی میکند که آیا در آینده نزدیک سکته مغزی در بیماران رخ میدهد یا خیر. با استفاده از روش رگرسیون لجستیک، عوامل خطر اصلی سکته مغزی شناسایی و میزان بروز آنها پیشبینی شده است. در این مطالعه اطلاعات بالینی از 5411 بیمار جمعآوری و پس از اعمال روش LR، مدل پیشبینیکننده طراحی شد. Manuscript profile -
Open Access Article
177 - A Review of Urban Growth Prediction Models
Fatemeh Hajizadeh Abdolrasoul Salman MahinyHuman population continues to aggregate in urban centers, who inevitably increases the urban footprint with significant consequences for biodiversity, climate, and environmental resources. Urban growth prediction models have been extensively studied with the overarching MoreHuman population continues to aggregate in urban centers, who inevitably increases the urban footprint with significant consequences for biodiversity, climate, and environmental resources. Urban growth prediction models have been extensively studied with the overarching goal to assist in sustainable management of urban centers. Despite the extensive research, these models are not frequently included in the decision making process. The survey found a strong recognition of the models’ potential in decision making, but limited agreement which these models actually reach enough potential in practice. This review aims are an overview of existing models, including advantages and limitations. Also, in general, it will be discussed to main reason for not applying these models in the decision making. Analysis of aggregated statistics indicates that cellular automata are the prevailing modeling technique, present in the majority of published works. Also, being unfamiliar decision-makers with models and thelack of popularity models to research are significant reasons for not using these models in the decision making. Manuscript profile -
Open Access Article
178 - Fire of Iranian forests, consequences, opposition methods and solutions
Saeedeh Eskandari سمانه اسکندریFire in the forests of Iran has destructed a large part of these valuable ecosystems in the recent years. Regarding to that Iran is one of the low-forest cover countries in the world, investigation of fire consequences in the forests of Iran and recognition of oppositio MoreFire in the forests of Iran has destructed a large part of these valuable ecosystems in the recent years. Regarding to that Iran is one of the low-forest cover countries in the world, investigation of fire consequences in the forests of Iran and recognition of opposition methods to fire in these forests is essential to present a solution to decrease these fires. Fire in the forests of Iran has had an important effect in destruction of unique flora and fauna, decrease of biodiversity and decrease of qualitative value of industrial plant species in addition to the economic damages and environmental pollutions. Furthermore, the recent fires in the forests of Iran have also increased the greenhouse gas emissions which it has an important role in the warming of these ecosystems and increasing of subsequent fires occurrence in these forests. This pre-background along with human-caused intentional and non-intentional fires in these ecosystems, has increased the continuous fires occurrence in the forests of Iran. Thus, development and designing of the effective opposition methods to these fires as preventing and operating methods is essential. Many different methods of fire occurrence and spread modeling have been developed using RS and GIS technologies which it seems that these methods have the effective role in predicting and preventing of these forests. Manuscript profile -
Open Access Article
179 - Evaluating the efficiency of artificial neural network in prediction of Electrical conductivity of Zarrinehroud River
Ali Khoshnazar Touraj Nasrabadi Pouyan Abbasi MaedehSixteen stations on Zarrinehroud River were sampled and parameters like temperature, alkalinity, Ph, electrical conductivity, dissolved oxygen and major anions and cations were measured on water samples. Afterwards, Pearson correlation coefficient between EC and other p MoreSixteen stations on Zarrinehroud River were sampled and parameters like temperature, alkalinity, Ph, electrical conductivity, dissolved oxygen and major anions and cations were measured on water samples. Afterwards, Pearson correlation coefficient between EC and other parameters were determined and the ones with lower cost of measurement were considered as the inputs of neural network models. Finally, the model number 5 with tangent Simulating algorithm and Levenberg-Marquet training Algorithm with minimum prediction error was accepted. The maximum determination coefficient, RMSE and NRMSE Were estimated to be 0.98, 168.33 and 0.28 respectively. Furthermore, it is observed that pH has a remarkable sensitivity more over 60 percent on the artificial neural network prediction. Manuscript profile -
Open Access Article
180 - Parameters of predicted changes in the Electrical Conductivity of groundwater in Tehran city with the help of neural network
Naser Mehrdadi Gholam Reza Nabi Bidhendi Akbar Baghvand Hamid Zare Abyaneh Pouyan Abbasi MaedehIn an attempt to examine the quality of ground water in Tehran with respect to the consumption pattern in the last ten years for 71 examination point, three distinct neural networks of different Electrical Conductivity (EC), input and output parameters were MoreIn an attempt to examine the quality of ground water in Tehran with respect to the consumption pattern in the last ten years for 71 examination point, three distinct neural networks of different Electrical Conductivity (EC), input and output parameters were set out . It is observed that, in order to forecast with a great deal of trial and error, the tangent algorithms with the momentum-training algorithm turns out to be less error. As the number of the input parameters is reduced and the training algorithm is fixed with momentum and the stimulating algorithm gives way to the tangent algorithm, error falls off. Finally, three model with one hidden layer, the momentum training algorithms and the stimulating tangent was constructed. The maximum error occurring implies the maximum determination coefficient of 0.986 that its connected to models 1 and 3. Moreover, in line with the neural network laid out in one layer, the minimum normal root mean square error (NRMSE) is supposed to run out at 0.110 in models 1 and 3. According to lesser input parameter of model number 2 and very close approximation to this two models (1and 3) with maximum determination coefficient of 0.96 and the minimum normal root mean square error (NRMSE) 0.176 can be a very close approximation and can decrease inputs parameters and experience for Measurement of input parameters and the estimate is supposed to be excellently acceptable. As regards the effect of the parameters on the forecast made, the neural network involves the predominance of the two sulphate and chloride ions over the sodium parameter. Manuscript profile -
Open Access Article
181 - Application of Artificial Neural Network and Regression Model to Predict the Phenomenon of Dust in the City of Ahvaz
Nabiollah Hosseini Shahpariyan Mohammad Ali Firozi Seyyed Reza Hosseini KahnojDust is one of the phenomena of destructive climate in the western provinces that causes great damage to the environment and many factors are involved in creating this problem. The aim of this study is to predict the phenomenon of dust in Ahvaz city. In this study, Ahv MoreDust is one of the phenomena of destructive climate in the western provinces that causes great damage to the environment and many factors are involved in creating this problem. The aim of this study is to predict the phenomenon of dust in Ahvaz city. In this study, Ahvaz synoptic data during the years (2000-2010) have been used. These data include mean dew point (in degrees Celsius), mean wind speed in knots, relative humidity in terms of average percentage and average monthly rainfall as input, and data on dusty days as target. Networks were introduced. Then, using causal modeling, the relationships between the variables are extracted and finally, the model is tested by neural network and stepwise regression model. The results confirm the ability of more than 74% of the model used to predict the dust phenomenon in Ahvaz. The regression rate of dust data in a linear combination with the variables entered in the equation is equal to 0.651. Also, the resulting coefficient of determination is equal to 0.424 and the modified coefficient of determination is equal to 0.410; That is, in fact, about 41% of the variance of the dust variable is explained and justified through independent variables. Manuscript profile -
Open Access Article
182 - Hegemonic worldview and its relationship with environmental Crises in the world
Reza Eltyaminia Ali Hosani In Islamic worldview, all humans and natures, together consist a part of entire of universe system. while in west cultures, only human are of essential values and nature is used as an instrumental value and a profiting source . according to political ecolog More In Islamic worldview, all humans and natures, together consist a part of entire of universe system. while in west cultures, only human are of essential values and nature is used as an instrumental value and a profiting source . according to political ecological belief, environmental issues will be solve if(when) fundamental changes is happen in the capitalist ideology and when a real democracy is prevailed and created in the countries of the world.so in this long with, aren naeis argue that pay attention to or take into consideration of ethical and religious traditions of the east could help us in protect of the environment and also we must believe that in the world, all alive creatures, in order to live, promotion and bloom, must have equal values and rights and nobody is save but everybody is saved. All humans are a part of nature not outside of it or upon it. (sakoee,2002,22).findings of the research show that the unreligious anthropologist and worldview and attitude and view based on humanism view and greed and avidity is causing many of environmental disasters and calamities. So, emendation or reformation of attitudes, believes and human view a bout human and environment within or in long with Islam systematic view could remove many of environmental and political issues and insecurities.This research while is studying the cultural and thought backgrounds causing environmental destruction under modernity and also with explanation of religious and cultural worldviews and their impacts on global ecology and environment, is looking for explanation and codification of Islamic environmental pattern to protect and preserve the balance of global and regional environment. the study is a basic and fundamental research and is used the Islamic realism and constructionist mean ology to do this research. Manuscript profile -
Open Access Article
183 - Methods of modeling and evaluation of fire occurrence risk in the forests of world and Iran
Saeedeh EskandariThe growing trend of forest fires necessitates presentation of a solution to predict and control them. Fire occurrence modeling with attention to all effective factors, is a proper solution to predict the fire occurrence in the forests because many factors affect on for MoreThe growing trend of forest fires necessitates presentation of a solution to predict and control them. Fire occurrence modeling with attention to all effective factors, is a proper solution to predict the fire occurrence in the forests because many factors affect on forest fire occurrence. This study has been done to investigate the different methods of fire modeling and fire risk assessment in forests of the world and Iran. Investigation of the researches implemented in Iran shows that the studies about fire risk potential evaluation in Iran have been limited and AHP has been used to weigh the effective factors in forest fire in most of these studies. Conclusion of researches implemented in the world shows that vegetation type, slope, aspect, distance from roads, topography and land use, have been the most effective factors in modeling of fire occurrence and integration of digital layers has often been based on a hierarchy and a risk coefficient in fire occurrence. The past actual fires map has been compared with the fire risk map to assess the accuracy of models used in provision of fire risk potential map. Logistic regression and decision-making tree algorithm have been used to select the effective variables in fire and to model the fire risk in some new studies. Integration of fuzzy inference system and neural network, neural intelligence and support vector machine has been used to predict the future fires in some advanced methods. Multi-criteria analysis is a subject used in the new studies and organization of the criteria in a spatial model using GIS has had the good results. Manuscript profile -
Open Access Article
184 - A Blind in Ma’arre, some Overexcited in Iran (A Comparaison of the Life, Poetry and Concerns of AbulAla’a Al-Ma’arri withThose of Khayyam and Sadegh Hedayat)
Hamid Reza ArdestaniTaking a look at the history of humankind we will come across the names of people whose lives have been different from the others. This difference has made the others not to know them correctly and everyone has described them according to his own view mostly becaus MoreTaking a look at the history of humankind we will come across the names of people whose lives have been different from the others. This difference has made the others not to know them correctly and everyone has described them according to his own view mostly because they had very complex characters. Among these great people in Persian language and literature are Hakim Omar Khayyam and SadeghHedayat. AbulAla’a Al-ma’arri is also another complicated literary character with similarities. The present article tries to compare the life, oetry and concerns of this literary man from Arabic culture with those of Omar Khayyam and SadeghHedayat in ersian literature. Manuscript profile -
Open Access Article
185 - A Comparative Analysis of Worldviews in Mythical and Epic Works of Shahnameh and Nibelungenlied
Masoud Salami Kambiz SafiieMyth and Epic as a genre in popular culture appeared prior to literature and have been closely tied to the nation’s literature. Despite many differences between men and cultures, their myths and epics are of great similarities. World literature is full of epic and MoreMyth and Epic as a genre in popular culture appeared prior to literature and have been closely tied to the nation’s literature. Despite many differences between men and cultures, their myths and epics are of great similarities. World literature is full of epic and mythic components. In Iranian and German literature also this issue is easily perceivable in Shahnameh and in Nibelungenlied’s song. In terms of cultural and linguistic aspects both are subsets of Hindu-Zhrmny languages add one could see a lot of similar components in them. This paper concerns firstly with the basic concepts and historical context of both them and then with the analysis of the worldviews and differences and features of these two everlasting works in Iranian and German literatures extensively. Manuscript profile -
Open Access Article
186 - Thought Sedative: Comparing Al-Maʿarri and Schopenhauer's Thoughts on Life
Alireza Alizadeh Asieh GhavamiWhat is the difference between the human life and animal's? Does he really have freedom and authority? If he has, does authority make his life easier? How much does instinct dominate his wisdom? Maʿarri and Schopenhauer are two philosophers and literates who answered th MoreWhat is the difference between the human life and animal's? Does he really have freedom and authority? If he has, does authority make his life easier? How much does instinct dominate his wisdom? Maʿarri and Schopenhauer are two philosophers and literates who answered the abovementioned questions. The present paper attempts to study some common thoughts of Abu al-ʿAlaʾ al-Maʿarri and Arthur Schopenhauer. Both had a kind of extreme realism toward life which usually known as pessimism. Both philosophers find life suffering and null but weren’t passive at all but tried to leave eternal works to calm down the ones who are thirsty to knowledge in different eras. The paper also tries to study their general thoughts about life comparatively. Manuscript profile -
Open Access Article
187 - Abul Ala Maari and Khayyam's Approach to Life and Death
Fatemeh Ghadami NajarkalaeiDeath, as one of the greatest mysteries of human life throughout history, has always been considered by thinkers. Abul Ala Moari, an Arab poet, thinker, and Khayyam Neyshabouri, an Iranian poet, philosopher, and scientist, were among the characters who thought a lot abo MoreDeath, as one of the greatest mysteries of human life throughout history, has always been considered by thinkers. Abul Ala Moari, an Arab poet, thinker, and Khayyam Neyshabouri, an Iranian poet, philosopher, and scientist, were among the characters who thought a lot about death. According to them, there are different perceptions of death. Positive and negative perceptions that are rooted in the philosophy of creation and the meaning of life, and without achieving the philosophy of life, it cannot have a correct perception of death. As a result, there is a deep connection between the meaning of life and death. With God's help, in this article, while presenting a biography of the two poets' life, we intend to study and analyze the thoughts, ideas, and aspects of similarities and differences between them, and to examine the views of these two people on the category of mortality and death. Manuscript profile -
Open Access Article
188 - Positive Thinking and its Functions from Holy Quran’s Perspective
Alireza ZolfaqariThe way of thinking plays an important role in human life and function. Human beings are distinguished from each other according to the kind of attitude they have towards God, the world and themselves and are divided into two groups: optimistic and pessimistic. Optimist MoreThe way of thinking plays an important role in human life and function. Human beings are distinguished from each other according to the kind of attitude they have towards God, the world and themselves and are divided into two groups: optimistic and pessimistic. Optimists do not take the events of the universe for granted. Because they know that every moment of the world has method and rule and without the will of God Almighty, not a leaf falls from a tree, and human beings should hope for God's mercy and forgiveness and plan and act happily. In the present study, the question is what are the psychological functions of positive thinking from the perspective of Holy Quran? psychological functions for positive thinking were concluded by studying the meanings of eleven Verse, which include strengthening theism, increasing physical and mental health, foresight and hope, managing emotions, effective communicating, increasing flexibility, increasing forgiveness, greater success, living happily, nobility and meaning of life and family support. Manuscript profile -
Open Access Article
189 - Anxiety Management and Psychological Teachings of the Holy Quran
mohammad hossain tavanayi farahnaz eshagh teymouri Abstract The emotional arousal associated with fear is known anxiety and stress that is of the major concerns of modern societies. In this article, using the verses of the Holy Quran and the opinions and views of the interpreters and different schools of psych More Abstract The emotional arousal associated with fear is known anxiety and stress that is of the major concerns of modern societies. In this article, using the verses of the Holy Quran and the opinions and views of the interpreters and different schools of psychology, we try to identify the nature and symptoms of anxiety and to review its management. Psychologists have practiced the anxiety management regarding the different schools of psychology such as psychoanalysis, behaviorism, and cognitive perspectives and deliver practical solutions such as free association, interpretation, transference, resistance, and removing regularly sensitivity and treatment of stable role. The Holy Quran has expressed this issue through symmetries such as: earthquake, tremble, awe, fear, fright, scare and ... and for relaxation and anxiety management has noted feeling and behavioral strategies such as: faith, remembrance of God and intimacy with the beloved one, the appeal of the unseen infinite power, trust, non-attachment to the world and .... . Manuscript profile -
Open Access Article
190 - ارزیابی گروههای اختصاصی agr در بین جدایههای استافیلوکوکوس اوریوس بدست آمده از حفره بینی گاو، گوسفند و بز با استفاده از مولتیپلکس PCR
حامد سلامی پرگو حبیب دستمالچی ساعی ملاحت احمدی حیدر رحیمی -
Open Access Article
191 - اثربخشی آموزش راهبردهای شناختی و فراشناختی بر خودکارآمدی و خوشبینی تحصیلی
میثم رادفر رضیه غضبانزاده منا هنرمند دربادام محبوبه موسوی -
Open Access Article
192 - بررسی رابطه رهبری توزیع شده با خوشبینی علمی معلمان ابتدایی مدارس پسرانه دولتی شهر تهران
امین هماینی دمیرچی سید محمد میر کمایی میترا عزتی -
Open Access Article
193 - پیشبینی رفتار شهروندی دبیران با توجه به میزان مشارکت در مدیریت (مطالعه موردی دبیران متوسطه شهرستان نقده)
صادق ملکی آوارسین کمال نقی پور -
Open Access Article
194 - تحلیل توزیع فضایی جمعیت استان زنجان طی سالهای 90-1365 و پیش بینی جمعیت تا سال 1404
محسن کلانتری کیومرث یزدان پناه سمیه نوری -
Open Access Article
195 - آﺷﮑﺎرﺳﺎزی ﺗﻐﯿﯿﺮات ﮐﺎرﺑﺮی و ﭘﻮﺷﺶ اراﺿﯽ در اﻓﻖ 2025 ﺑﺎ اﺳﺘﻔﺎده از ﻣﺪل اتوماتای سلولی CA (ﻣﻄﺎﻟﻌﻪ ﻣﻮردی: شمال شهر اصفهان)
اعظم خدادادی رحیم سرور مجید ولی شریعت پناهی -
Open Access Article
196 - The Study of Optimism and Hope in Bahar’s Odes Based on Positive Psychology
Fereshteh Gholamrezaie Nezad Anari Mahmoud Sadeghzadeh Hadi Heidary NiyaPositive psychology is one of the new branches of psychology. This science has three fundamental principles: 1) the study of positive emotions, 2) the study of positive traits, and 3) the study of positive institutions. Martin Seligman, the founder of this theory, belie MorePositive psychology is one of the new branches of psychology. This science has three fundamental principles: 1) the study of positive emotions, 2) the study of positive traits, and 3) the study of positive institutions. Martin Seligman, the founder of this theory, believes that a purposeful and meaningful life relies on six positive characteristics of wisdom, courage, altruism, justice, moderation, sublimity, and positive emotions and in three paths of satisfaction, pride, and peace of the past, long-lasting happiness, enthusiasm, and enjoyment from the present, and optimism, hope, and trust in the future. This study examined the poems of Malek osh-Sho'arā Bahār in descriptive, documentary, analytical, and quantitative evaluation manners and in regards to the element of optimism and hope from the positive psychological perspective. By extracting and examining the evidences from one hundred poems of Divan-e Bahār, we discovered that 83 of them have positive themes, half of which are devoted to optimism and hope with a higher frequency than despair and disappointment. Meantime, the poet has referred to the subject of complaint and sorrow in only seven poems. Despite all personal and social agonies and pains, Bahār is a positive thinking, self-flourishing, and optimistic poet. He is another example of the great men in Persian culture and literature. He has written and composed poetry to improve the environment and create a better and happier society. His craft and mission many years ago are an instance of new science that claims to provide new strategies for the better living of human beings. Manuscript profile -
Open Access Article
197 - Translation of Death in Hossein Monzavi’s Worldview
Shiva Abazar Tooraj AghdaieDeath as an absolute necessity, bound to happen, is unique and belongs to human beings. Whatever we know of death is assured, or at least seems to be the most absolute knowledge of us as human beings. It is an inescapable reality that all creatures will experience it la MoreDeath as an absolute necessity, bound to happen, is unique and belongs to human beings. Whatever we know of death is assured, or at least seems to be the most absolute knowledge of us as human beings. It is an inescapable reality that all creatures will experience it later or sooner. The humankind worldview of death is based on his attitudes towards life. Some people believe that it is attractive and fascinating, while others find it horrible and disgusting. It is clear that the way people try to believe in death has roots in their lifestyles and attitudes towards life. Hossein Monzavi, aka “The King of Ghazal”, the famous poet of 1960s and 1970s, could revive ghazal and made it enthralling and romantic. Some of Monzavi’s ghazals are about death, and he attempts to reveal his attitudes towards the concept of death as a bound to happen. He sometimes believes in death doubtlessly, and sometimes fights it. Despite some contradictions in some of his ghazals about death, he doesn’t believe in death as something absurd and conjectural. This paper aims, through an analytical- descriptive method and by investigating Monzavi’s ghazals, to study his worldview and understanding of death. Manuscript profile -
Open Access Article
198 - تحلیل رابطه خوشبینی با امید به زندگی و شادکامی کارکنان
مریم تقوایی یزدی منظر صادقی -
Open Access Article
199 - نقش حالتهای فراشناختی در پیش بینی اضطراب ریاضی دانش آموزان
ارسلان خانمحمدی ابوذر ناصری -
Open Access Article
200 - رابطه بین سلامت سازمانی و مسئولیتپذیری اجتماعی با نقش میانجی خوشبینی تحصیلی در معلمان
ابوالقاسم بریمانی امکلثوم جعفری -
Open Access Article
201 - پیشبینی حمایت اجتماعی کارکنان بر اساس متغیرهای انعطافپذیری و خوشبینی
ابوالقاسم بریمانی Yasman Modanloo Razyeh Goli -
Open Access Article
202 - Predicting the social support of Staff based on the variables of flexibility and optimism
Razyeh Goli Yasman Modanloo Abu al-Qasim BarimaniS Social support is the establishment of a social interaction that, through continued communication, leads to empathy and ultimately to a safety net for the individual and helps him or her feels better about himself or herself. The purpose of this study is to determine MoreS Social support is the establishment of a social interaction that, through continued communication, leads to empathy and ultimately to a safety net for the individual and helps him or her feels better about himself or herself. The purpose of this study is to determine the Predicting the social support of Staff based on the variables of flexibility and optimism. The statistical population consisted of 250 employees of the health center in Sari. Sample size according to Morgan and Krejcy table, 148 individuals were selected randomly (gender). The instrument for collecting data was three standard Questionnaires of Dennis & Vanderwall Flexibility, Noori Optimism and Sherborne & Stuart Social support. The validity of the tool is confirmed by the experts and Specialists. Their reliability for each respectively was 0.83, 0.80 and 0.96. For data analysis, descriptive statistics and inferential statistics of Pearson correlation and multiple regressions were used. The results of the research showed that: There is a relationship between flexibility (r = 515) and optimism (r = 0.392), with social support of employees; and the share of flexibility and optimism is different in predicting the social support of the employees. Also, the flexibility, optimism, and social support of employees Based on gender were not different. Manuscript profile -
Open Access Article
203 - رابطه بین سلامت سازمانی و مسئولیتپذیری اجتماعی با نقش میانجی خوشبینی تحصیلی در معلمان
ام کلثوم جعفری ابوالقاسم بریمانی -
Open Access Article
204 - Optimism & Pessimism Biases in Earnings Forecasting and Deviation in Financial Reporting: Evidence of Subjectivism and Opportunistic Unethical Behavior of Managers
Mohammad Hassani Amir Hossein Haji AmiriUnder a challenging business environment, assessing the managerial decisions about earnings forecasting and earnings reporting is important and the evidence indicates the occurrence of managers’ subjectivism in these areas. In this regard, analyzing the managers' MoreUnder a challenging business environment, assessing the managerial decisions about earnings forecasting and earnings reporting is important and the evidence indicates the occurrence of managers’ subjectivism in these areas. In this regard, analyzing the managers' behavior about earnings forecasting and earnings reporting can be explained through the signaling approach and opportunistic approach. This study assessed the relationship between optimism & pessimism biases in management earnings forecast and financial reporting distortion by focusing on managing the reported earnings to determine which of these approaches prevails in the surveyed firms. Management earnings forecast biases are measured using the pattern proposed by Cheng & Firth, (2000); also, the model presented by Dechow et al (1995) is used to assess the management incentives to manage earnings using discretionary accounting procedures & estimates.Research samples include 198 firms listed in Tehran Securities & Exchange over the period 2012-2018. Using multivariate regression models based on panel data, evidence indicated that there is a meaningful and positive relationship between management earnings forecast bias and financial reporting distortion using the earnings management based on discretionary accruals. This result indicates an interest conflict and occurrence of unethical opportunistic behavior due to the high subjectivism of managers. Also, the type of optimistic and pessimistic bias in management earnings forecast is meaningfully related to accruals-based earnings management; so, the motivation of managers to manage earnings in an optimistic situation is more than pessimistic. In addition, results of the test for equality of means between series showed that there is a meaningful difference between the means of earnings management based on discretionary accruals in optimistic and pessimistic earnings forecast situations. Manuscript profile -
Open Access Article
205 - The Impact of Managers’ Narcissism on Their Trade Strategies and Innovative Acts with an Emphasis on Their Optimism
Nazanin Bashirimanesh Younes Hamid Nasrin GhadamyariThe purpose of the present study is to review the impact of managers’ narcissism on their trade strategies and innovative acts with an emphasis on their optimism. The research population includes all accepted corporations in Tehran Stock Exchange during the years MoreThe purpose of the present study is to review the impact of managers’ narcissism on their trade strategies and innovative acts with an emphasis on their optimism. The research population includes all accepted corporations in Tehran Stock Exchange during the years from 2015 to 2019. Using a systematic removal method, 101 corporations were chosen as the statistical sample and data analysis was conducted by EViews and Minitab software. For hypothesis testing, multivariate linear regression was used. The results showed that there is a significant correlation between managers’ narcissism and their aggressive and defensive strategies while the variable of their optimism has no significant effect on the relationship between their narcissism and aggressive strategies. Furthermore, there is a significant correlation between managers’ narcissism and components of innovative acts including personal innovation, environmental innovation, administrative innovation, and technical innovation and managers’ optimism is effective on the correlation between this variable and all components of innovative acts, except technical innovation. The results of this study can lead to an effect on decision-making and identify the impact of psychological components such as narcissism on people’s performance. Manuscript profile -
Open Access Article
206 - A Study of the Effect of Auditing Committee on the Relationship between Investors’ Short-Sightedness and Research and Development Costs
AliReza Ghanbarzadeh Behbahani Mohammad Abedi Zoheyr AlipourzadehPurpose: Investors’ short-sightedness is a factor that makes them overestimate short-term and underestimate long-term interests. This behavior of investors motivates the directors to overestimate short-term performance of the company by decreasing its research and MorePurpose: Investors’ short-sightedness is a factor that makes them overestimate short-term and underestimate long-term interests. This behavior of investors motivates the directors to overestimate short-term performance of the company by decreasing its research and development costs. On the other hand, the auditing committee as a powerful mechanism of corporation authority makes a contribution to supervise responsibility of the board of directors through surveillance of the financial reporting process, autonomy of auditors, and effectiveness of internal controls. In this regard, the present research aims to review the effect of auditing committee on the relationship between investors’ short-sightedness and research and development costs in corporations accepted in Tehran Stock Exchange,Method: The information of 150 companies were collected and analyzed by systematic deletion method during a 7-year-old period from 2007 to 2013. Hypotheses testing was conducted using multivariate regression and ordinary least square method with mixed data.Results: Investors’ short-sightedness has a significantly negative impact on research and development costs. It means that as investors’ short-sightedness increases, research and development costs decline. The results also showed that the size of the corporation's auditing committee has a significantly decreasing impact on the negative relation between investors' short-sightedness and research and development costs and makes the correlation between those two variables positive. The autonomy of the corporation's auditing committee has a moderating effect on the negative correlation between investors' short-sightedness and research and development costs and decreases its intensity. It means that the decrease in the size and autonomy of the auditing committee decreases the negative relation between investors' short-sightedness and research and development costs.Conclusion: Considering the negative effect of investors' short-sightedness on research and development costs that encourages the directors to decrease long-term investment in future research and development, it is suggested to the managers to regard long-term consequences of decreasing investment in this field because they will decline the corporation's performance and competitive strength in long-term. Furthermore, it is recommended to short-sighted investors who have short-term perspective to pay more attention to the real and long-term performance of the company rather than its short-term interests because investors' short-sightedness causes that fundamental factor and long-term perspective in terms of investment in stock exchange be forgotten and replaced with obtaining just daily profit. Therefore, investors' short-sightedness has caused one of the greatest problems in the stock exchange and in the long term leads to its inefficiency. Manuscript profile -
Open Access Article
207 - An Estimation of Customer Lifetime Value Based on Quality of Services in Mashhad Body Building Gyms
Seyed Mohammad Hosein Hoseini Ravesh Amir MoghaddamThe purpose of the present study is to review an estimation of customer lifetime value (CLV) based on quality of services provided by Mashhad body building gyms. The research method was correlational description and it had an estimation approach. The Research statistica MoreThe purpose of the present study is to review an estimation of customer lifetime value (CLV) based on quality of services provided by Mashhad body building gyms. The research method was correlational description and it had an estimation approach. The Research statistical population consisted of those who enrolled in body building gyms in Mashhad for at least 6 months, among whom 384 members were studied in different gyms ranked from 1 to 3 with respect to their cooperation and accessibility. The research instruments consisted of 2 standard questionnaires including Services Quality by Parmason et al. (1985) and Customer Lifetime Value by Vow Vali (2011) which were distributed among the customers in the gyms through a stratified way. SPSS and LIZREL software programs were used for data analysis. The results showed that by 95% confidence level it can be said that quality of services provided by the gyms can have a significantly positive effect on CLV while no significant correlation was observed between CLV and ranking of the gyms. On the other hand, quality of services and ranking of the gyms have a significant impact on CLV. Therefore, it is recommended to the directors of the gyms to pay more attention to the components which enhance service quality and ranking of their gyms. Manuscript profile -
Open Access Article
208 - The relationship between organizational bullying and organizational silence with organizational pessimism in the employees of the General Department of Sports and Youth of Fars
omid safari gholamreza safariThe purpose of this research was to determine the relationship between organizational bullying and organizational silence with organizational pessimism among the employees of the General Department of Sports and Youth of Fars. This research is applied and descriptive an MoreThe purpose of this research was to determine the relationship between organizational bullying and organizational silence with organizational pessimism among the employees of the General Department of Sports and Youth of Fars. This research is applied and descriptive and correlational. The statistical population of this research was all the employees of the General Directorate of Sports and Youth of Fars in the number of 114 people, of which 94 people cooperated with the researcher as a sample and using the total number sampling method. To collect data, the standard questionnaires of Inarsen et al.'s (2009) organizational bullying, Dimitris and Kola's (2008) organizational silence, and Din et al.'s (1998) organizational cynicism were used. Descriptive statistics methods were used to describe the data, and Pearson's correlation coefficient and regression statistical methods were used to analyze the data. The results showed that there was a positive and significant relationship between organizational bullying and organizational silence with organizational cynicism, and also organizational bullying and organizational silence have the ability to significantly predict subjects' organizational cynicism. (P ≤ 0.01). Manuscript profile -
Open Access Article
209 - Short-Term Load Forecasting using an Ensemble of Artificial Neural Networks: Chaharmahal Bakhtiari Case
E. Faraji M. Mirzaeian H. Parvin A. Chamkoorii Majid MohammadpourShort-term load forecasting is very important in electrical marketing. Load forecasting is dependent on climatic condition of every region and the previous structures of electrical consumption in that region; so we have accomplished this through employing climatic data MoreShort-term load forecasting is very important in electrical marketing. Load forecasting is dependent on climatic condition of every region and the previous structures of electrical consumption in that region; so we have accomplished this through employing climatic data (including temperature and pressure) and real load consumption of Chaharmahal Bakhtiari. We have evaluated our method using four machine learning algorithms: artificial neural networks (multilayer perceptron), ensemble of artificial neural networks, support vector machine and ensemble of support vector machine. Experimental results indicates that ensemble of artificial neural networks is superior to the others in the field of load consumption forecasting of Chaharmahal Bakhtiari. Manuscript profile -
Open Access Article
210 - Analysis of the Behavior of Individual Investors Based on the Theory of Planned Behavior: With Emphasis on Optimism-Pessimism and Financial Literacy
Mohammad Nazaripour Babak ZakizadehAmong the requirements for capital markets development is to analyze the individual investors' behavior from the different aspects. In this study, the individual investors' behavior has been investigated based on the expanded theory of planned behavior (including two va MoreAmong the requirements for capital markets development is to analyze the individual investors' behavior from the different aspects. In this study, the individual investors' behavior has been investigated based on the expanded theory of planned behavior (including two variables: optimism-pessimism and financial literacy). The required data were collected through the distribution of questionnaires among 266 individual investors. Data analysis was performed using structural equation modeling in the form of SmartPLS version 3 and SPSS version 26 software. According to the research findings, all 10 research hypotheses were confirmed. Out of 10 hypotheses, 7 are related to direct effects and 3 are related to indirect effects. This means that the variables of attitude, subjective norms, perceived behavioral control, and optimism-pessimism have a positive and significant effect on people's investment intention. In addition, variables of optimism-pessimism and financial literacy have a positive and significant effect on attitude. Also, the variable of financial literacy has a positive and significant effect on the variable of perceived behavioral control. Based on the research findings, the variables of attitude and the perceived behavioral control have a mediating effect on the relationships between optimism-pessimism and financial literacy variables with people's investment intention. Finally, based on the research findings, the implementation of the extended planned behavior theory in the capital market can help the growth and development of this market. Manuscript profile -
Open Access Article
211 - The Effect of CEO Optimism and Myopia on Dimensions of Corporate Risk Management Moderated by CEO Political Connection and Efficiency
Javad Zanganeh majid ashrafi Ebrahim Abbassi Arash NaderianThe CEO behavioral pattern is the most important factor in decisions regarding corporate financing and capital structure composition. With the increasing competitiveness and management difficulty in highly complex organizational environments, firms (companies/organizati MoreThe CEO behavioral pattern is the most important factor in decisions regarding corporate financing and capital structure composition. With the increasing competitiveness and management difficulty in highly complex organizational environments, firms (companies/organizations) require CEOs who can identify and consider such inherent complexity in momentous decisions. Risk management constitutes a major part of this decision-making process. Therefore, this study sought to address how CEO’s optimism and myopia affect different dimensions of corporate risk management, including compliance, strategy, operation, and reporting, considering the moderating role of CEO’s political connection and efficiency. To this end, the data were collected from 130 firms listed on Tehran Stock Exchange in the 2014–2018 timeframe, and they were analyzed using multivariate regression with combined data. Results (from hypothesis testing) showed that CEO’s optimism has a negative relationship with strategy and operation, but a positive one with reporting. They also revealed that there is a negative, significant relationship between CEO’s myopia and strategy and compliance. CEO’s political connection turns negative the relationship between CEO’s optimism and operation as well as the relationship between CEO’s myopia and compliance; in addition, it has a positive effect on the relationship between CEO’s optimism and compliance and strategy, and a negative one on (the relationship with) operation. The mediating role of CEO’s efficiency is positive in the relationship between myopia and strategy and reporting, and it is negative in the relationship of myopia with operation. Manuscript profile -
Open Access Article
212 - Investigating Time Varying Herd Behavior in Tehran Stock Exchange: Generalized Autoregressive Score Approach
Mohammad Ebrahim Samavi Hashem Nikoomaram Mahdi Madanchi Zaj Ahmad YaghobnezhadHerd behavior is one of the most important behavioral biases in financial markets and is one of the determinants of financial crises. Given that herd behavior directly affects price, presenting a model based solely on past prices, with good predictability, indicates the MoreHerd behavior is one of the most important behavioral biases in financial markets and is one of the determinants of financial crises. Given that herd behavior directly affects price, presenting a model based solely on past prices, with good predictability, indicates the existence of market herd behavior. This article aims to investigate the existence of herd behavior in Tehran Stock Exchange and presents a new nonlinear variable time model called Generalized Autoregressive Score (GAS) and has been compared with traditional GARCH and AR nonlinear models. in order to predict the distribution of return of the total index of the stock exchange during the period 2010 to 2020. The results of modeling for the asset by the new GAS model are compared with the results of the GARCH and AR models and their performance is tested for inside and outside the sample. ample in the internal and external tests show that the new GAS model is more accurate than the traditional GARCH and AR models in predicting the daily return distribution of the total index of the Tehran Stock Exchange and also the presence of herd behavior in Iran's capital market has been approved. Manuscript profile -
Open Access Article
213 - The fields of philosophic pessimism and discouragement in Iraj Mirza's education and lyrical poems
Ali Bali Ali Asghar HalabiPessimism or despair is a psychological condition which occurs in people's rational and emotional area, and is common in almost every society. A sharp form of this which is seen in poets and the enlightened is called "philosophical despair". The bases of this condition MorePessimism or despair is a psychological condition which occurs in people's rational and emotional area, and is common in almost every society. A sharp form of this which is seen in poets and the enlightened is called "philosophical despair". The bases of this condition can be sought in the people's personal life events and the society's political, social and economical transitions. In the beginning of the twentieth century and after the failure of the constitutional movement, parts of the hearts of poems turned into pessimism and despair. Iraj Mirza is one of the prominent poets of this era whose thoughts and literary works are affected by despair and pessimism. The bases of this pessimism are under the influence of the unkindness of friends, the death of the young child, the lack of societal situations, the loss of governmental positions and the decline of the aristocratic place of his family. Manuscript profile -
Open Access Article
214 - رابطه خوشبینی و بدبینی با سلامت روان در افراد بزرگسال شهر اصفهان
اصغر آقایی راضیه رئیسی دهکردی سیدحمید آتش پور -
Open Access Article
215 - The Role of Cognitive Emotion Regulation Strategies in the Prediction of Depression
azam salehiThe goal of the present study was to determine the role of cognitive emotion regulation strategies in predicting depression. In this correlation study, 262 Isfahan Payame noor University students from different fields were selected by multi-stage random sampling method. MoreThe goal of the present study was to determine the role of cognitive emotion regulation strategies in predicting depression. In this correlation study, 262 Isfahan Payame noor University students from different fields were selected by multi-stage random sampling method. Cognitive Emotion Regulation Strategies Questionaire (Garnefski et al., 2002) and SCL-90 (Derogatis et al., 1973), Were administered. Research data were analyzed by Pearson correlation coefficient and stepwise regression. The results of stepwise regression analysis showed that from among of the nine scales of cognitive emotion regulation strategies scale, catastrophizing, acceptance, refocusing on planning, rumination, and recent stress, respectively, influence and significantly predict depression (P < 0.001). But, self-blame, blaming others, positive reappraisal, positive refocusing and putting into perspective strategies had no effect on depression and were removed from the equation. These results provide guidelines for the prevention of depression through modification of cognitive emotion regulation strategies. Manuscript profile -
Open Access Article
216 - Prediction of Internet Addiction,Based on Emotional Intelligence Among Isfahan University Students
nasim jafari maryam fatehizadeThe aim of this research was to investigate the predictive role of emotional intelligence in internet addiction among Isfahan university students. This is a multiple correlation research. The statistical population included students of Isfahan university of Iran. The MoreThe aim of this research was to investigate the predictive role of emotional intelligence in internet addiction among Isfahan university students. This is a multiple correlation research. The statistical population included students of Isfahan university of Iran. The randomly selected training samples included 71 students (36 girls and 35 boys). Assessment instrument consisted of Internet Addiction Test Young (1998) and Trait Emotional Intelligence Questionnaire Petrides and Furnham (2001). The gathered data was analyzed by descriptive and inferential statistics and regression methods. The results showed that there were correlations (r=-0.54) between internet addiction and emotional intelligence (P < 0.001) and emotional intelligence can predict 29% of internet addiction (P < 0.001) . Manuscript profile -
Open Access Article
217 - Comparison of the Effectiveness of Attribution Training, Metaphor Training, and Attribution/metaphor Training on Optimism of School Students
galavizh alizade rasool kord noghabi najme nazariThe purpose of this study was to compare the effectiveness of attribution training, metaphor training, and attribution/metaphor training on students optimism . This semi- experimental study was conducted with pretest - posttest and control group. Statistical populatio MoreThe purpose of this study was to compare the effectiveness of attribution training, metaphor training, and attribution/metaphor training on students optimism . This semi- experimental study was conducted with pretest - posttest and control group. Statistical population included all first grade state and day high school girl students in Hamadan in the academic year 2010-11 (1389-90s.c.) and the sampling method was multistage cluster sampling. The sample was comprised of 96 students and subjects were randomly assigned into the four groups of 24 persons each (3 experimental grups and 1 control group). The research instrument was the Optimism Questionnair (Oleary & Fincham, 2000). Experimental treatment was conducted on the experimental groups during 10 sessions and then posttests were administrated on the 4groups. Statistical analysis was conducted by one-way analysis of variance and LSD test using SPSS-16 software. Results showed that there is a difference among all methods effectiveness except metaphor effectiveness as compared with attribution and attribution effectiveness as compared with control, on improving optimism in the first grade high school girl students (P < 0.001). Also, when the effectiveness of these three methods were compared, it was found out that the most effective methods were metaphor / attribution, metaphor and attribution respectively. These findings show that metaphor training and attribution/ metaphor training leads to optimism improve students. Therefore using new training such as metaphor and attribution/metaphor can reduce the current and future difficulties of students. Manuscript profile -
Open Access Article
218 - The Relationship between Resilience and Psychological Well-being: The Mediating Role of Optimism
hossein souri Elahe Hejazi محسن سورینژادThe present study was carried out in order to predict psychological well-being via resiliency and test the mediating role of optimism in the relationship between psychological well-being and resilience. To this end, a sample of 414 students of medicine (213 boys and 1 MoreThe present study was carried out in order to predict psychological well-being via resiliency and test the mediating role of optimism in the relationship between psychological well-being and resilience. To this end, a sample of 414 students of medicine (213 boys and 191 girls) was selected through multistage cluster sampling. They were asked to Complete Resiliency Scale (Connor & Davidsons, 2003), Optimism Scale (Scheier and Carver, 1995) and Well-being Scale (Ryff, 1989). The results indicated that resilience can predict psychological well-being. The results showed that correlation of optimism with predictive variable (resilience) is positive and significant (P < 0.01, r=0.38) and with the criterion variable (psychological well-being) is also positive and significant (P < 0.01, r= 0.45). According to the results of hierarchical regression, it may be concluded that optimism plays a partial mediating (and not full) role in the relationship between resiliency and psychological well-being. Based on the findings it can be said that part of the effect of resiliency on, psychological well-being could be applied through optimism. The findings showed that regardless of the level of resilience, optimism can, to some extent, facilitate psychological well-being. All correlations were significant in the level of 0.01. Manuscript profile -
Open Access Article
219 - Psychometric characteristics of positive psychological capital scale among staff employees of education in Isfahan
azam rajaei mohammad ali nadi alireza jafariThis study has been implemented to evaluate the psychometric characteristics of the Positive Psychological Capital Scale. The population of this study consisted of all staff of six education districts in the year of 1394 that 325 of them were sampled by share-based stra MoreThis study has been implemented to evaluate the psychometric characteristics of the Positive Psychological Capital Scale. The population of this study consisted of all staff of six education districts in the year of 1394 that 325 of them were sampled by share-based stratified random sampling based on sample size formula, Cohen et al (2000) and were taken Positive Psychological Capital Scale Luthans et al (2007). Research used Cronbach's alpha coefficient for the reliability, and confirmatory factor analysis for the validity based on Structural Equation Model. Cronbach's alpha coefficient for positive psychological capital scale was 0/89 and for optimism, hope, resilience, and self-efficacy subscales in order were 0/70, 0/83, 0/73, and 0/87. results of one factor and four factor confirmatory analysis based on Luthans et al theoretical model showed that four factor model has more favorable goodness of fit indexes than one factor model. Fit indexes are favorable. The correlation between total positive psychological capital scale with optimism, hope, resiliency and self-efficacy factors respectively is 0.76, 0.87, 0.88, and 0.84, which shows a good validity. The correlation between the factors is between 0.41 and 0.62, which is significant at level (P <0.01). In order to evaluate the differential validity of the positive psychological capital scale, simultaneous implementation of Counterproductive Workplace Behavior (CBW) scale was used. The result showed that the positive and negative anticipatory capital scale had a negative correlation (-0.39). There is no significant difference between the positive psychological capital of the staff of the six education areas at level (P <0.05), but there is significant difference between the level of psychosocial capital of the male and female education staffs in the level (P <0.05). Based on these results, this scale which has reliability and validity can be considered for future researches. Manuscript profile -
Open Access Article
220 - The contribution of spiritual health, optimism and happiness in prediction of psychological well-being among students
fatemeh farhadyan azam moradiThe purpose of this study was to determination the contribution of each of the variables of spiritual health, optimism and forgiveness to predict the psychological well-being of the students of Payam-e-Noor University of Dolatabad Center. The research sample consisted o MoreThe purpose of this study was to determination the contribution of each of the variables of spiritual health, optimism and forgiveness to predict the psychological well-being of the students of Payam-e-Noor University of Dolatabad Center. The research sample consisted of 120 students from among 1477 students of different faculties of this university who were selected randomly and in a cluster sampling. The research method was correlation of the predicted type.The instruments were, the Rif questionnaire (1980), the Spiritual health questionnaire from the viewpoint of Islam Mousavi Moghaddam (1392), Carver & Shire (LO), Life Inventory (LOT) questionnaire (1985) and ehteshamzadeh (2010) Interpersonal Forgiveness Inventory (IFI) (2010) used.Data were analyzed using descriptive statistics and stepwise regression analysis.The findings showed that the average psychological well-being of students was 62.61%. The results of stepwise regression analysis also showed that spiritual well-being significantly predicted the psychological well-being of students (P = 0.0001). But the addition of each of the variables of optimism and forgiveness to the spiritual health variable does not significantly increase the predictive power of psychological well-being of the students. The results of the hypothesis test showed that psychological well-being had a significant relationship with spiritual well-being, optimism and forgiveness of students. Manuscript profile -
Open Access Article
221 - The relationship of psychological capital (hope, optimism, resiliency and self-efficacy) with the achievement goals and academic performance of the first-year students
mohammad hossein mohebi nooredinvand Maniji shehni yeilagh hassan pasha sharifiThe purpose of this study was analyzing the relationships of psychological capital (PsyCap) with achievement goals and academic performance of the first-year university students of Islamic Azad University in Masjed Soleiman and Ahwaz branches. The participants were cons MoreThe purpose of this study was analyzing the relationships of psychological capital (PsyCap) with achievement goals and academic performance of the first-year university students of Islamic Azad University in Masjed Soleiman and Ahwaz branches. The participants were consisted of 520 students (262 males and 258 females) who were selected by using the stratified random sampling method. The used instruments in the present study were consisted of Adult Dispositional Hope Scale (ADSH), Life Orientation Test-Revised (LOT-R), Resiliency Scale (RS), and Academic Self-Efficacy Scale (ASES) in order to assess each of the four factors of making up psychological capital. The Patterns of Adaptive Learning Scales (PALS) and Andrew Achievement Goals Scale were used to measure the achievement goals. The average of student's final scores in that semester was used to measure the academic performance. For analyzing the data, the confirmatory factor analysis, Pearson correlation coefficient and multiple regression methods were applied. The results showed that psychological capital and its four components with mastery-approach and performance-approach goals, and also academic performance had a meaningful positive relationship. Moreover, psychological capital and its four components had negative relationship with performance avoidance goal. Achievement goals had meaningful relationship with academic performance as well. In addition, the combination of the four variables of hope, optimism, resiliency and self-efficacy with respect to higher order construction of psychological capital can predict the mastery- approach goal and academic performance of the students more effectively. Manuscript profile -
Open Access Article
222 - The Relationship between Meta-Cognitive and Achievement in Special Texts in English Course of the University Students
فروغ تنساز محترم نعمتطاووسیThis study aimed to assess the effects of meta-cognition on educational achievement of the Azad university students in special texts in English language. After the final examination, 32 students with the higher grades and 32 students with the lower grades from the 128 MoreThis study aimed to assess the effects of meta-cognition on educational achievement of the Azad university students in special texts in English language. After the final examination, 32 students with the higher grades and 32 students with the lower grades from the 128 students of the 4 classes were chosen and their meta-cognitive skills were compared. In this research, meta-cognitive skills were considered as independent variables, academic achievement as the dependent variable and sex as the control variable. The result showed a significant difference between strong and weak group according to the meta-cognitive levels. In addition, the sub-scales scores (awareness, cognitive strategy, planning and self-control) were significantly different in two group. Manuscript profile -
Open Access Article
223 - Predicting locational trend of land use changes using CA-Markov Model (Case study: Kohmare Sorkhi, Fars province)
Sara Azizi Ghalati Kazem Rangzan Javad Sadidy Peyman Heydarian Ayoub TaghizadehLand use changes act as a significant factor in the environmental changes and have become a global threat. Monitoring and prediction these changes by satellite images and models can help the planners and managers to make more conscious planning decisions. In this regard MoreLand use changes act as a significant factor in the environmental changes and have become a global threat. Monitoring and prediction these changes by satellite images and models can help the planners and managers to make more conscious planning decisions. In this regard, the current research aimed to monitor, model and predict land use changes using CA-Markov model in Kohmare Sorkhi region, Fars province in 2024 for a period of 25 years (1987-2012). To implement the mentioned model, the land use map was first prepared by ETM+ and TM sensors during three years (1987, 2000, 2012). Then, validation of maps and change detection process were performed. The results of change detection for the first period (1987-2000) and second period (2000-2012) with an accuracy of 83% and Kappa index of 88% have shown the greatest increase in the rangeland area (4224.24 ha) and the greatest decrease in the forest area (3953.75 ha). In the next stage, in order to calibrate the CA-Markov model, land use map for 2012 was predicted; on the other hand, regarding Error Matrix between the modeling land use map and the reference land use map, the Kappa index wad given as 75%. Finally, considering the previous stage, the land use map for the outlook of 2024 was predicted. The final results for 2024 indicated that the forest area would endure the great amount of changes in comparison with 2012. The forests would change into the irrigated agricultural area and rangelands which can be considered in sustainable development planning by decision makers. Manuscript profile -
Open Access Article
224 - Monitoring and forecasting of land use change by applying Markov chain model and land change modeler (Case study: Dehloran Bartash plains, Ilam)
Seyed Reza Mir Alizadehfard Seyedeh Maryam AlibakhshiNowadays modeling and forecasting of land use changes by application of satellite images can be a very useful tool for describing relations between natural environment and human activities to help planners to make decisions in complicated conditions. There are various m MoreNowadays modeling and forecasting of land use changes by application of satellite images can be a very useful tool for describing relations between natural environment and human activities to help planners to make decisions in complicated conditions. There are various methods for forecasting of land uses and coverage, in which the Markov chain model is one of them. In this research, land use changes in Bartash plain in Dehloran which is located in Ilam province in the area of 135244 hectares in 3 time periods (1988, 2001 and 2013) of landSat satellite images, providing land use map in 6 classes (low density forest, medium-dense grassland, poor grassland, agricultural, alluvium sediments and non-vegetated lands) by application of Kohonens neural network and also Markov anticipation model and Land change modeler (LCM) approach was predicted for the year 2030. The classification results showed the rate of demolition and a reduction of the area of low density forests and medium grassland land uses and increase in area of other land uses. Reduction of low density forest and the medium grassland area and increasing growth of other land uses demonstrated the overall destruction in the region and replaced with poorer land uses. At the end, by application of the Markov chain model and LCM modeling approach, land use changes were a forecasted for the year 2030. The results of changes anticipation matrix based on maps of years 2001 and 2013 showed that it is likely that in the period of 2013-2030, 45% of low density forest, 71% of medium grassland, 96% of poor grassland, 81% of agricultural lands, 93% alluvialvium sediments and 100% of non-vegetated lands remain changeless; non-vegetated lands have the most stability and low density forest have the least stability. Manuscript profile -
Open Access Article
225 - Forecasting of forest land changes in the Chaloosrood watershed
Vajiheh Ghorbannia Kheybari Mir Mehrdad Mirsanjari Mohsen ArminDeforestation affects watershed processes and biochemical cycles and lead to soil erosion and lack of water in the catchment areas. This study is aimed to investigate the changes in forest land in the Chaloorood watershed on the west of Mazandaran province using Geomod. MoreDeforestation affects watershed processes and biochemical cycles and lead to soil erosion and lack of water in the catchment areas. This study is aimed to investigate the changes in forest land in the Chaloorood watershed on the west of Mazandaran province using Geomod. In this study, maps of forest in the years of 1987 and 2015 were prepared using satellite images. Then the suitability forest map was produced by making a regression equation between suitability criteria maps and forest changes map in the period of 1987-2015. Finally, by using forest map in 1987, forest suitability map and the number of modified pixels in forest land between 1987 and 2015, Forecast of the forest map for 2043 was done using Geomod. Also, by using the Validate function and classified forest map 2015, as a reference map, and the forecasting forest map 2015, as a comparative map, the validity of the production map was evaluated. The results showed that the area of forest land in 1987, 2015, and 2043 was 38683.65, 2464.354 and 15227.25 hectares, respectively. The extent of forest changes in the last 28 years and the next 28 years is 35.72% and 38.76% respectively. Forest changes in the period between 1987 and 2015 under the influence of factors such as distance from the road, forest cover density, distance from the village, slope and elevation above sea level, respectively. The Pseudo R2 and ROC coefficients are 0.29 and 0.85 respectively, which indicates the proper ability of the model to estimate forest changes over the past 28 years and the relative agreement of the model with the real changes. In this study the accuracy of resulting land use maps was 96%, which represent the appropriate capability of Geomod in land use changes modeling in Chaloosrood watershed. Manuscript profile -
Open Access Article
226 - Monitoring and prediction land use/ land cover changes and its relation to drought (Case study: sub-basin Parsel B2, Zayandeh Rood watershed)
Shahin Mohammadi Khalil Habashi Saeed PormanafiLand use and land cover (LULC) change because of its impact on natural ecosystems has become a concern for natural resources protectors and managers. The present study aimed to predict LULC changes and also to study the relation of drought with these changes in the sub- MoreLand use and land cover (LULC) change because of its impact on natural ecosystems has become a concern for natural resources protectors and managers. The present study aimed to predict LULC changes and also to study the relation of drought with these changes in the sub-basin Parsel B2 with an area of 21100 hectares using CA-Markov model and Standard Precipitation Index (SPI). For this purpose, using the preprocessed images of the sensors TM, ETM+, and OLI for the years 1986, 2001 and 2016, respectively, the LULC map was provided with supervised classification and maximum likelihood method. To validate the CA-Markov model, the LULC maps have been predicting for 2016 and they were compared to the reference land use map of 2016. After ensuring the accuracy of the predicted results for the year 2016, the related land use and land cover maps were predicted for the year 2030. The result showed a relation between LULC changes and drought condition. Based on result predicted for the year 2030, rain-fed agriculture 6.95% increase and range land 6.66% decrease in area. Thus In the event of drought and abandonment rain-fed agriculture land, soil erosion, increasing and also grazing pressure on the remaining range land causing range land degradation. Therefore, if the current land use strategy with current management remain, land degradation in the region will be inevitable. Manuscript profile -
Open Access Article
227 - Monitoring and predicting land use changes using landsat satellite images by Cellular Automata and Markov model (Case study: Abbasabad area, Mazandaran province)
Amer Nikpour Hamid Amounia Elahe NourpasandiBackground and ObjectiveToday, land use change in many countries has become an important challenge that has many effects on the environment. Accordingly, the study of land use change at different scales is one of the important issues in the proper management of natural MoreBackground and ObjectiveToday, land use change in many countries has become an important challenge that has many effects on the environment. Accordingly, the study of land use change at different scales is one of the important issues in the proper management of natural resources and environmental change at various levels. Therefore, being aware of land use changes and investigating their causes and factors in several time periods, and predicting land use changes in the future can be properly planned to reduce adverse effects, which has been considered by planners and city managers. They help in land use planning. Also, converting land uses to each other and changing the use of vegetation is known as an important issue. Therefore, the purpose of this study is to monitor and predict land use changes and land cover in Abbasabad urban area in the future; Using these changes, appropriate management measures can be taken to preserve and rehabilitate lands. Materials and Methods A combination of an automated cell model and Markov chain in the Abbasabad urban area was used to predict land use change; The relevant images were taken from the TM and OLI sensors of the Landsat 8 and 5 satellites at the USGS site. Four user classes, including zone class built with code number 1, vegetation class with code number 2, water resources class with code number 3, and barren land class with code number 4, were separated for Abbasabad urban area. Obtained USGS. In order to extract land use classes, after checking several methods, object-oriented classification method and support vector machine (SVM) algorithm were used due to better efficiency. Evaluation of Babian satellite imagery classification The overall accuracy and kappa coefficient were performed for three periods of time. Each of these classified maps was evaluated by drawing an error matrix. 250 sample points were used to prepare this matrix. The type of sampling was stratified sampling. Also, to determine land use changes in 2030, classified maps were used and with the help of TerrSet software, changes made in classes and their percentages were obtained, and using the CA-MARKOV model, changes of different classes based on matrices. The possibility of transfer was predicted. Results and Discussion The results during 1997, 2006, and 2017 show that the constructed area has an increasing trend and the uses of vegetation, barren lands, and water resources have a decreasing trend and 23279 hectares of lands in the region are built area dedicated. The kappa coefficient calculated for 1997, 2006, and 2017 is 0.86, 0.89, and 0.89, respectively. Markov chain forecasting model with 85% accuracy stated that the trend of land use change for 2030 will be the same as in previous years, and this indicates that the conversion and change of land uses will proceed as before, and it is necessary to mention this point that the identical uses of vegetation to vegetation cover the largest area during the years 2006 to 2017, and this shows that in this area, vegetation is still stable and has undergone less changes. Conclusion The output of the 13-year forecast map for 2030 in this study indicates the appropriate accuracy of the CA-MARKOV model. In addition, this output shows that this method can be trusted for short-term planning. These forecast maps can be a good guide for managers and urban planners. To achieve better results, it is recommended to use a combination of automated cell model and Markov chain to monitor and predict changes nationwide. The results of this study, in addition to helping to reduce the volume of input data, but also in the processing of classified images and in predicting them for the future. Manuscript profile -
Open Access Article
228 - Study and prediction of land surface temperature changes of Yazd city: assessing the proximity and changes of land cover
Mohammad Mansourmoghaddam Iman Rousta Mohammadsadegh Zamani Mohammad Hossein Mokhtari Mohammad Karimi Firozjaei Seyed Kazem AlavipanahBackground and Objective The expansion of urbanization has increased the scale and intensity of thermal islands in cities. Investigating how cities are affected by these thermal islands plays an important role in the future planning of cities. For this purpose, this stu MoreBackground and Objective The expansion of urbanization has increased the scale and intensity of thermal islands in cities. Investigating how cities are affected by these thermal islands plays an important role in the future planning of cities. For this purpose, this study examines and predicts the effect of land cover (LC) changes in the three classes of LC including urban areas, barren lands, and vegetation on land surface temperature (LST) in the city of Yazd during the last 30 years using Landsat 5 and 8 images. This study also examines the effect of the ratio of proximity to the barren land and vegetation classes during this period to examine how the recorded LST is affected by the mentioned ratio.Materials and Methods The LC maps of Yazd city were extracted using a supervised Artificial Neural Network classifier for 1990, 2000, 2010, and 2020. Terrestrial data, google earth, and ground truth maps were used to derive training data. The LST of Yazd was obtained from the thermal band of Landsat 5 and Landsat 8. After that, the LST was classified into six available classes, including 16-20, 21-25, 26-30, 31-35, 36-40, and 41-46°C which has shown that the four last classes play an important role in LST changes in Yazd city during last 30 years. To evaluate the effects of the proximity of barren land and vegetation LC classes on the LST recorded by the sensor, firstly the proximity ratio was calculated in 5×5 kernels for all image pixels. Then the mean of LST was derived based on this ratio of barren and vegetation lands.Results and Discussion The results of this study showed that in Yazd city, from 1990 to 2020, the area of the urban area has grown 91.5 % (33.6 km2) over the last 30 years. Barren and vegetation land, have negative growth in the area over the same period. From 1990 to 2020, barren lands in Yazd experienced a growth -79.4% (21.3 km2), which the sharp growth of urban areas justifies this negative growth in barren lands. Vegetation classes in Yazd from 1990 to 2020, have experienced a growth -68.5% (12.2 km2). The average ground temperature of this city has been constantly increasing during these 30 years. By 2020, the city of Yazd, reaching an average of 38.1°C compared to 29.2°C in 1990, has experienced a 30.4% increase in its average LST. The temperature classes of this city have also moved towards warmer temperature classes in these 30 years. As the main part of the LST area of Yazd, in 1990, in the first place, the class of 26-30 °C with 47 km2 and at the second place the class of 31-35 °C with 26.4 km2 are classified. In 2000, in a reverse trend, the main LST class was 31-35°C with 52.8 km2 as the first place and the 26-30°C class with 20 km2 as the second place. With an increased class, the LST class of 36-40 °C for both 2010 and 2020 with 40.2 and 63 km2 respectively has been recorded as the largest LST class. The LST class of 31-35 °C has been recorded as the second LST class of both years with 33.2 and 9.7 km2, respectively. The difference between these two years is in the growth -70.7% (23.5 km2) of the class area of 31-35°C and the increase of 10.3% (0.8 km2) of the hottest class of the statistical period, 41-46°C, in 2020, compared to 2010. The results of this study also showed that the highest average temperature in all year was recorded for barren lands at 37.3°C. Also, a positive correlation (mean correlation 0.95) was shown between the proximity to barren land cover and the mean LST. However, the sharp upward trend of urban areas in the whole statistical period (91.5% with 33.6 km2) as the second class with the highest average LST after the barren lands with an average of 34.1 °C versus a downward trend of 79.4% (21.3 km2) of barren lands has increased the average LST over a statistical period of 30 years. It is because the decrease of 68.5% (12.2 km2) of vegetation areas as an LC class with the lowest average LST (32.2°C) in the same period, neutralized the effect of decreasing barren lands and intensified the trend of increasing the LST. Meanwhile, a negative correlation (mean correlation -0.97) was established between the ratio of proximity to vegetation and the average LST. The results of forecasting land cover changes in 2030 in the city of Yazd indicate that in a process similar to previous periods, the class of urban areas will increase. This growth will not be significant compared to 2020, with 1.6% (1.1 km2). However, a significant decrease in green areas (vegetation) by -19.6% (1.1 km2) in the same period, along with a slight decrease in barren lands -1.8% (0.1 km2) will cause the earth’s surface to become warmer, and the area of LST classes will be increased by the year. Accordingly, the main area of the LST class in 2030 for the city of Yazd, as in 2020, is forecasted 36-40°C with 58.2 km2 (-7.6% growth compared to 2020). But the dramatic growth of the hottest class of LST over the statistical period (41-46°C) with 166.3% (14.3 km2) growth as the second major class of LST in this year (2030), as well as the negative and dramatic growth of the relatively cooler class 31-35°C with -97.9 % (9.5 km2) in this year indicates the warmer ground surface temperature in 2030.Conclusion The results of this study indicate that in 30 years in Yazd city, the decrease in vegetation in the first place, along with the increase in urban areas in the second place, has caused an increase in LST. Thus, the vegetation class reduces the LST due to its cooling effect considering its water content. In this study, it was shown that by taking all factors into account, the reduction of barren lands will lead to a decrease in LST, and also increasing urban areas with a lower impact factor than barren lands will increase the LST. However, the decrease in the area of green lands (vegetation) in recent years, along with the sharp increase in the area of urban areas has caused an increase in LST. Increasing the proximity to vegetation by creating green areas by increasing the ratio of vegetation in the vicinity of different LC and also reducing the area of barren lands, can be a good solution to deal with the impact of urbanization in recent years on ground surface temperature. Manuscript profile -
Open Access Article
229 - Monitoring Bakhtegan wetland using a time series of satellite data on the Google Earth Engine platform and predicting parameters with Facebook’s Prophet model
Mohsen Dastaran Shahin Jafari Hossein Moslemi Sara Attarchi Seyed Kazem AlavipanahBackground and Objective Wetlands are habitats for vegetation and wildlife and because of this, they have a high environmental value. Also, wetlands reduce soil erosion, restore aquifers, store rainwater in a flood event, and provide water for agriculture or livestock. MoreBackground and Objective Wetlands are habitats for vegetation and wildlife and because of this, they have a high environmental value. Also, wetlands reduce soil erosion, restore aquifers, store rainwater in a flood event, and provide water for agriculture or livestock. Wetlands are vulnerable to human interventions and changes such as drainage, urban sprawl, infrastructure development, and over-exploitation of groundwater resources. Prediction of the condition of wetlands in the future requires a correct understanding of the evolution of wetlands and identifying their trend of change. Nowadays, Remote Sensing technology is widely used for mapping wetlands, and its ability to monitor the changes in wetlands regardless of the diversity of wetlands has significantly increased the value of this science in this field. Remote Sensing can be an effective means of simulating and predicting wetland degradation processes by providing images at different times and through dynamic spatial modeling. In this study, the changes in the Bakhtegan wetland have been monitored. This wetland has high environmental and tourism importance and its drying affects negatively the living conditions and health of local people as well as tourism in the region. In addition, predictions of precipitation parameters, groundwater level, and temperature have been conducted. For this purpose, the Google Earth Engine platform was used to capture and process images. Google Earth Engine is a platform that can capture and process images in the shortest time and at high speed. In this regard, using Google Earth Engine, changes in the lake water area along with changes in temperature, groundwater level, and precipitation were extracted and monitored. Moreover, a comparison took place between these parameters to determine the changes that have taken place in the lake over the past two decades. To predict the parameters, the changing pattern was predicted and analyzed using the Prophet model. The most important advantage of the Prophet model is its ability to convert discrete data to continuous data to make the best predictions. This method automatically detects the trend of seasonal data and displays the trend of seasonal changes.Materials and Methods Satellite images were acquired from the Google Earth Engine platform to monitor the wetland. Landsat 7 and 8 images were used for water body extraction, GRACE Data were used for extraction of groundwater level changes, MODIS product was used for extraction of vegetation and wetland surface temperature, and TRMM image product was used to extract precipitation values. An automated water extraction index was used to extract the wetland body water. The groundwater level was extracted from the GRACE sensor. MODIS sensor product was used to obtain the surface temperature time series for the study area. For the extraction of precipitation time series, the monthly cumulative data of the TRMM (3B43V7) satellite with a spatial resolution of 0.25°C was extracted using Google Earth Engine and the trend of changes was evaluated and analyzed. The Mann-Kendall test is one of the most widely used non-parametric tests for detecting meteorological and environmental data trends, which is used to detect a monotonic trend line since this test is a non-parametric method, it does not need that the data follow a normal distribution. The Prophet predictive model is a predictive library developed by Facebook and is available in R and Python programming languages. This library supports additive modeling methods and can properly predict discrete values continuously. This feature is called "Holiday". Another feature of this library is the automatic detection of daily, weekly, seasonal and annual trends. The mean absolute error (MAE), by default, exists in the Prophet library. This error represents a more natural standard than the mean error and unlike the RMSE error, it is unambiguous.Results and Discussion In the present study, we monitored the Bakhtegan wetland using the Google Earth Engine platform to observe the trend of water level changes in this wetland from 2000 to 2020. In addition, Parameters were also predicted using the Prophet Prediction method which is developed and published by Facebook. By examining this trend, it can be observed that the water level of the wetland has been significantly reduced during two decades. In this regard, the trend of groundwater level, temperature, and precipitation in the area was investigated. Examining these factors, it was found that along with a 58.3% decrease in the water level of the wetland, there was a 260% decrease in the groundwater level of the region, although the amount of rainfall in the region has been less compared to other factors and has been decreased about 29%. Using Mann-Kendall statistical test, the trend of this decline was proved. To predict the parameters, the Prophet model has been able to make predictions for 1500 days as continuous data using discrete data. The output of the model has shown that for rainfall parameters and groundwater level a downward trend is predictable over the next 1500 days which is low intensity for precipitation but with high intensity for groundwater level. Temperature prediction indicated that it has a seasonal trend, and has a high amount of fluctuation within a year, but its annual trend indicates stability in the coming years. The results of the model for the water level of the wetland also show a relatively low upward trend that has a probability of change of ±12.5 Square kilometers. Also, the error of the parameters at the 95% significant level has acceptable accuracy, which indicates the validity of the prediction. An automated water extraction index was used in this study to extract the time series of the water body of the wetland. Using the mean time series extracted, the maximum and minimum wetland’s water body area belongs to 2006 with 629.23 square kilometers and 2014 with 156.82 square kilometers, respectively. The time series of changes in this wetland indicates that the water volume of the wetland has been declining in the last two decades. According to this study, it can be concluded that the trend of changes in the water level of the wetland has been decreasing. The descending changes in the lake based on the trend of changes in groundwater levels indicates a decrease in water volume in the area. Considering that the trend of precipitation changes has been stable, it can have assumed that improper management and excessive use of groundwater may be a reason for lowering the water level of the wetland. Due to the same decrease in the water level of the lake, the temperature has also decreased by about 3°C.Conclusion According to this study, it can be concluded that groundwater levels and precipitation will have a downward trend in the future, which will lead to a decrease in the water level of the wetland, which itself has the potential to fluctuate in the future, and the downward trend continues. With the current trend, the only solution is to plan properly to preserve the wetland. If this trend continues, we will face the destruction of the wetland. Given the monthly trend of the wetland surface, it is suggested not to over-exploit groundwater resources, especially in the summer. For further research, the Google Earth Engine platform can be used without the need to download the images and spend a lot of time and money, to obtain the time series of images. Regarding the prediction, in future studies, the Prophet model can be applied, since it uses discrete data and at the same time provides the desired accuracy. Manuscript profile -
Open Access Article
230 - Monitoring and prediction of spatial and temporal changes of landuse/ cover (Case study: Marave Tappeh region, Golestan)
Asghar Farajollahi Hamid Reza Asgari Majid Ownagh Mohammad Reza Mahboubi Abdol-Rasoul Salman MahiniIn this research, land use changes in previous years and the possibility of predicting in the future using Markov chain model were investigated in the Maraveh Tappeh region of Golestan province. Therefore, using images of MSS, ETM+ and OLI sensors of LandSat satellite a MoreIn this research, land use changes in previous years and the possibility of predicting in the future using Markov chain model were investigated in the Maraveh Tappeh region of Golestan province. Therefore, using images of MSS, ETM+ and OLI sensors of LandSat satellite and using ancillary information, land use maps of 1986, 2000 and 2014 was provided and land use map of 2024 was predicted. According to the results, dense forest area decreased during the study period and with passing time but the area of agricultural land increased with the passage of time while the dense rangeland area decreased during the period 1984-2000. The annual growth rate of agricultural land has achieved 113.45 ha during the period 1984-2000 and this change value was obtained 91.27 ha for the period 2000-2014. The results of predicting changes in the time interval 2014-2028, showed it is possible that will be decreased semi-dense forest and dense rangelands and will be increased other land-use areas according to results of model predictions. The highest increase will be belonging to agricultural land use that will be increased to 25.89 ha per year. According to research findings, land-use changes are causing degradation of natural resource areas. However, in recent years, have taken effective actions to protect these areas, but more attention and protection of natural resources and environment in the Marave Tappeh region is essentially still. Manuscript profile -
Open Access Article
231 - Application of spatial statistics in zoning and spatial analysis of the sound speed in the Persian Gulf
Mahyar Majidy Nik Hamed DeldarThe aims of this study were to find the distribution of sound speed under the influence of water's physical parameters; to predict spatial analysis in oceanography using geostatistical methods; to forecast value parameters for the Persian Gulf and zoning the sound speed MoreThe aims of this study were to find the distribution of sound speed under the influence of water's physical parameters; to predict spatial analysis in oceanography using geostatistical methods; to forecast value parameters for the Persian Gulf and zoning the sound speed. Sound Speed was calculated using Chen-Millero formula and pressure, salinity, and temperature data. The data extracted from World Ocean Atlas 2013 with regular mesh grid 0.25 degree. Sound speed was calculated using the Chen-Millero formula. Spatial analysis of the sound speed comparison based on three methods Kriging, Co-Kriging and Inverse Distance Weighted. These methods were performed using GS+ software in both warm and cold season. The best method finally used to forcast and prepare the plans of zoning sound speed. The Pearson’s correlation test was performed between independent variables and sound speed showed that the maximum correlation occurs between temperature and sound speed. Therefore, the temperature was considered as the auxiliary variable in Co-Kriging method for spatial analysis of sound speed. Cross-validation results showed that model's forecasting in cold season was better compared to warm season in this region. Results of spatial analysis showed that the sound speed decreased about 20m/s in all layers from the Hormuz Strait toward the northwestern part of the Persian Gulf. Because of the increased salinity the maximum of sound speed was always in the south shallow area. In all investigated stations, sound speed reduced with increasing depth, due to temperature reduction and the sound channel is not also observed. Manuscript profile -
Open Access Article
232 - Land use change modeling using artificial neural network and markov chain (Case study: Middle Coastal of Bushehr Province)
Mehdi Gholamalifard Mohsen Mirzayi Sharif Joorabian ShooshtariCoastal lands of Bushehr Province has a high importance in terms of marine exporting and importing, oil and gas reserves, agriculture, nuclear plant, suitable condition for fishing and tourist attractions. Therefore new desirable methods for monitoring and modelin MoreCoastal lands of Bushehr Province has a high importance in terms of marine exporting and importing, oil and gas reserves, agriculture, nuclear plant, suitable condition for fishing and tourist attractions. Therefore new desirable methods for monitoring and modeling changes are required to be used in these areas. This study was performed with the aimed of monitoring and modeling land use changes using Artificial Neural Network (ANN) and Markov Chain in Land Change Modeler (LCM) in 23 years period (1990-2011). After model accuracy assessment using kappa coefficient, land cover map of the year 2016 was predicted by the 2006-2011 calibration period. The results indicated that two trends include changes from open lands to agricultural and then quitting these agricultural lands have been observed during the study period. Such that, the agricultural area has increased to 19715.76 hectares from 1990 to 2006,but between 2005 to 2011, only 14.48% of agricultural lands has remained unchanged and the large area of those were finally left. In this study, LCM was able to predict 0.76 of changes correctly. So that it was predicted 12000 hectares increasing of extent urban development in the coastal lands of Bushehr Province in 2016. Manuscript profile -
Open Access Article
233 - Monitoring, assessment and prediction of spatial changes of land use /cover using Markov chain model (Case study: Bostagh Plain - South Khorasan)
Kamran Karimi Choughi Bayram KomakiMonitoring and optimal management of natural resources is requiring an update and accurate information. In this context, land use/cover maps is considered as a one of the most important sources of information on natural resources management. Optimal management of resour MoreMonitoring and optimal management of natural resources is requiring an update and accurate information. In this context, land use/cover maps is considered as a one of the most important sources of information on natural resources management. Optimal management of resources requires assessment and understanding of the changes and degradation of resources in the past. It also needs to have an accurate plan in order to control and inhibition of the happened destruction potential in future. The Markov chain model is one of the most efficient methods for predicting changes in land use and land cover. In this research, land cover changes in previous years and the possibility of predicting in the future are investigated in Bostagh plain using the Markov chain model. Therefore, using MSS (1987), ETM+ (2002) and OLI (2014) images sensors and region ancillary information, land use map is provided and 2024 land use map is predicted too. Land use maps were performed using kappa coefficient after correcting satellite images, determining training samples, and evaluating classification accuracy. According to the results, bare/barren and rangeland classes are the most dynamic existing usage in the region. The area percentage of these lands during 1987 to 2014 was 21.64% subtractive and 31.14% additive respectively. This represents a total degradation and replacement of the weaker use in the region. The results of predicting changes in the time interval 2014-2024, showed that 98% of residential lands, 88% of bare land, 77% of saline land, 45% of rangeland, and 37% of agriculture will remain unchanged. Moreover, the conversion of rangeland to bare land (41.94%) are the highest, and the conversion of bare lands to residential lands (0.02%) and rangeland to residential lands (0.03%) are the lowest possibility of conversion. Predicting maps derived from the Markov chain model are very important to provide an overview for better natural resources management. Landuse changes Satellite images Predict of changes Markov chain model Bostagh plain Manuscript profile -
Open Access Article
234 - Adaptive analysis of graphical structural metric for anomaly detection in social networks
Mojtaba Aajami Naser AsgariIntroduction: Social networks are exposed to a variety of security problems due to their wide use and popularity. Therefore, identifying unusual activities in social networks is of paramount importance as it helps to obtain significant information about the behavior of MoreIntroduction: Social networks are exposed to a variety of security problems due to their wide use and popularity. Therefore, identifying unusual activities in social networks is of paramount importance as it helps to obtain significant information about the behavior of unusual users and identify them. One of the important aspects of social network analysis is to check the presence of anomalies. Anomalies in the field of social networks imply irregular and often illegal behavior. A host of methods have been proposed to detect different kinds of anomalies in social networks. According to the employed approach, these methods can be classified into three categories, namely, clustering-based, based on network structure-based, and signal processing-based. In this paper, we extend the graph structure-based approach by introducing and analyzing important graph metrics to detect abnormal activities. Theoretical and experimental evaluation using several large data sets demonstrate that the relationship between the interface node and the number of edges helps to correctly detect and rank the maximum number of anomalies.Method: The proposed method is a combination of graphical and statistical theory. First, various metrics and graph structures are calculated, and then statistical methods are used to identify and analyze unusual structures (stars and clusters).Results: Statistical and visual analysis shows that the area covered by the curve is maximum for the interface (B) compared to the number of edges (E). The results show that the proxy is a scale that can correctly detect many abnormalities. It can also be said that the relationship between the (B) and the (E) helps to predict most anomalies.Discussion: In this research, a structure-based method was presented by using graph criteria to predict abnormalities. The curve fitting method based on the graph structure was extended to detect anomalies using the combination of new graph criteria. It was observed that the relationship between the interface and the edges helped to predict a large number of anomalies that were either misclassified or missed by the Oddball method and the ABC relationship to E. The abnormality scores assigned to the nodes help predict the degree of anomalies and rank the nodes according to their irrational behavior. Manuscript profile -
Open Access Article
235 - Comparison of Linear and Non-linear Support Vector Machine Method with Linear Regression for Short-term Prediction of Queue Length Parameter and Arrival Volume of Intersection Approach for Adaptive Control of Individual Traffic Lights
mohammad ali kooshan moghadam Mehdi Fallah TaftiIntroductionThis study was carried out in line with the development of adaptive traffic signal control systems to provide a better traffic control at intersections. In this approach, if the predicted data related to the future cycles are used to optimize the upcoming sc MoreIntroductionThis study was carried out in line with the development of adaptive traffic signal control systems to provide a better traffic control at intersections. In this approach, if the predicted data related to the future cycles are used to optimize the upcoming schedule, it will control the traffic in unforeseen cases and manage it before reaching the forthcoming cycles. In order to have enough data to create such a model, the required data from two intersections in Yazd city were collected and these intersections were simulated using AIMSUN software. Then these intersections were calibrated and validated for existing conditions. The prediction accuracy results were extracted by the proposed methods and compared with the linear regression method. RMSE, MAE and GEH errors were used to compare the methods.Method: The predicted queue length and arrival volume parameters for any entry approach of itersections are major variables required during the adaptive signal control process, Hence, Linear and Non-linear Support Vector Regression Methods combined with the time series method were used to predict these parameters. For comparison of the performance of these models with a conventional model, Linear Regression models were also developed for the prediction of these parameters.ResultsFor the developed model based on combined Linear Support Vector Regression and the time series methods, the number of optimal previous cycle data used in the model was measured as 6 and 2 previous data cycles for predicting the arrival volume at Pajuhesh and Seyed Hassan Nasrollah intersections, respectively. The optimal number of previous data used in the model was measured as 9 and 11 previous data cycles for predicting the queue length at Pajuhesh and Seyed Hassan Nasrollah intersections, respectively. Also, using the combined Non-Linear Support Vector Regression and the time series methods, the number of optimal previous data cycles was obtained as 8 and 2 cycles in predicting the arrival volume at Pajuhesh and Seyed Hassan Nasrollah intersections, and the number of optimal previous data cycles was obtained as 7 and 7 cycles in predicting the queue length at Pajuhesh and Seyed Hassan Nasrollah intersections.Discussion: The results of RMSE, MAE and GEH measures were used to compare the performance of the developed models with the real data. This comparison indicated that the model based on the combined Non-Linear Support Vector Regression and time series methods, has produced the best performance in predicting traffic arrival volume than the other aforementioned models. However, in terms of predicting the queue length, this model produced a better performance than the combined Linear Support Vector Regression at only one of the intersections. The Linear Regression model produced the weakest performance in all comparisons. Thus, it can be concluded that the combined Support Vector Regression and time series methods are appropriate tools in predicting traffic parameters in these situations. Manuscript profile -
Open Access Article
236 - A Similarity Measure for Link Prediction in Social Network
Ali Sarabadani Kheirollah RahseparFard Seyed Morteza PournaghiIntroduction: A social network is a social structure made up of individuals or organizations. Social network analysis is an approach in which the network is considered as a set of nodes and relationships between them. Nodes are individuals and actually actors in the net MoreIntroduction: A social network is a social structure made up of individuals or organizations. Social network analysis is an approach in which the network is considered as a set of nodes and relationships between them. Nodes are individuals and actually actors in the network and the relationships between them are displayed as connections between nodes.Method: Among many social network analysis issues, link prediction has attracted much attention due to the growing number of social network users. Link prediction means predicting which new interaction is going to happen in the future. Traditional link prediction methods considered pairs of nodes as a unit and made decisions based on commonalities between them. In addition, we proposed a new similarity measure for link prediction in social networks.Results: We compared this criterion with four prediction methods of Jaccard link, Salton Index, Salton Cosine, and resource allocation). Experimental runs in this article were carried out on five social network datasets. Our results showed that this criterion performed better than other link prediction techniques on all datasets.Discussion: Social network analysis has recently attracted lots of attention among researchers due to its wide applicability in capturing social interactions. Link prediction, related to the likelihood of having a link between two nodes of the network that are not connected, is a key problem in social network analysis. Many methods have been proposed to solve the problem. Among these methods, similarity-based methods exhibit good efficiency by considering the network structure and using as a fundamental criterion the number of common neighbors between two nodes to establish structural similarity. Manuscript profile -
Open Access Article
237 - Face Recognition in Images Using Viola_Jones Method and Image Texture Analysis
Mahdi Hariri Narmineh HeydarzadehIntroduction: Face recognition is one of the most important biometric technologies for people identification, also used in access control. Face recognition is one of the important steps before identity recognition. Usually, one method is used to detect the presence of f MoreIntroduction: Face recognition is one of the most important biometric technologies for people identification, also used in access control. Face recognition is one of the important steps before identity recognition. Usually, one method is used to detect the presence of faces in images. Still, in this research, to increase the accuracy of detection, the combination of two methods is used to improve the detection performance: Viola-Jones algorithm and the matching of image components and texture with face and skin components. In the first step, we use the Viola-Jones algorithm to detect the facial features. In the next step, the features of the eye and nose tissues are analyzed with regression neural networks, and facial features are recognized better according to the facial features. In this research, the texture features of the right and left eyes and the nose of the face are used to increase the matching accuracy. We have used the faces of the FDD-Fold dataset to evaluate the proposed method. Comparing the performance of this method with the RCNN deep network method with a much smaller number of training data, we reached an accuracy of 96.36%, more than the deep learning network. This method gives good results in systems with limited computing ability and average amount of data.The face recognition system is one of the biometric identification systems and one of the most important technologies for people identification, which is also used in access control. Face identification is one of the few biometric methods that, with the advantages of high accuracy and low level of human intervention, is used in cases such as information security, law enforcement and monitoring, traffic control, and registration in attendance systems. This method creates more convenience and development with fewer requirements. then, this method has received more attention during the last twenty years.Face detection is a local binary classification problem that shows the presence of faces in the given image using boxes surrounding them. Although the Viola-Jones method is less accurate than modern methods such as convolutional neural networks; Its much lower efficiency and training parameters compared to the millions of parameters of a typical CNN result in faster training, better accuracy with limited data, and its use in devices with limited computing power such as cameras and mobile phones. The innovation of this method is matching the geometric pattern of the edges to identify the presence of the face in the image, along with matching the skin texture. This method seems to be faster and more accurate than the previous ones.Method: In this research, in the first step, we use Viola-Jones, one of the optimal face recognition algorithms in the image, to detect facial components. In the next step, we use the adaptation of the general shape of facial parts such as eyes, and match the textures in the image with the predicted texture for human skin, to improve the recognition performance and increase the recognition accuracy, in such a way that the regression neural networks examine the eye and nose tissue characteristics and according to the characteristics of the facial tissue, the facial components are recognized by the regression neural network. The investigated features in the texture include minimum and maximum color intensity, mean and median, and variance of the image. The data is given to the regression neural network for training. Here Remarkable thing is matching the overall shape of the human head and face, and in the next step matching the overall shape of the facial parts such as the eyes to improve the accuracy of the presented method. We also use the matching of textures in the image with the texture predicted for human skin to further improve the accuracy of the program's performance. Manuscript profile -
Open Access Article
238 - Study Effects Of Hydroalcoholic Extract Of Medicago sativa in the Treatment Of Acetic Acid Induced Gastric Ulcer in Rats
Mahdi Margani Hamed Alizadeh Sina AghshahiInroduction and Objective:Peptic ulcer, from histologicalpointisknownasmucosalnecrosisfactor. The purpose of this study was to investigate the effect of Alfalfa hydroalcoholicvegetivearial organs extract on gastric ulcer induced by acetic acid in Rat.Material and Method MoreInroduction and Objective:Peptic ulcer, from histologicalpointisknownasmucosalnecrosisfactor. The purpose of this study was to investigate the effect of Alfalfa hydroalcoholicvegetivearial organs extract on gastric ulcer induced by acetic acid in Rat.Material and Methods: In this experimental study, 60 wistar rats weighting approximately (200-250g) were randomly divided into 4 groups; control, sham(normal salin), experiment 1 (extract of dose 250 mg/kg body weight) and experiment 2 (extract of dose 500 mg/kg body weight). Rats were deprived of food and then underwent surgeryand gastric wasby injecting60% acetic acid after 4,7,10,14 days gavage, the rats' stomach out and then measuring the wound and fixed with 10% formalin, the passage of the tissue section was stained And the number of neutrophils, macrophages and fibroblasts were counted.Results:Results showed that the hydroalcoholic extract of Alfalfacaused a significant increase in gastric ulcer healing in experimental groups 1 and 2 (PConclusion:Alfalfahydroalcoholic vegetive arial organs extract is effective in the treatment of peptic ulcer induced by acetic acid Manuscript profile -
Open Access Article
239 - Designing a conscious prediction system based on future literacy: social constraints in sport for all
Javad shahvali kohshouri Hadiseh BahramiObjective: Objective: After explaining the relationship between constraints and future research, one of the things that are effective in predicting or even making future in all areas is future literacy. It can be acknowledged that future literacy is a scientific skill t MoreObjective: Objective: After explaining the relationship between constraints and future research, one of the things that are effective in predicting or even making future in all areas is future literacy. It can be acknowledged that future literacy is a scientific skill that develops a better understanding of the predicted assumptions. Future literacy or future is an educational framework that makes it possible to visualize the approaches for the future.Health-centric exercise or sports for all are sports activities that are followed by the vitality of joy and health at the level of different societies. Future or lost literacy is a valuable futures study in sports. Therefore, the aim of the present study is to design a general informed forecasting system based on future literacy, which in this study was specifically tested on public sports.Methodology: This qualitative research, which is exploratory-fundamental in nature, with a focus on social constructivism and using the constructivist approach of the basic theory, presents a short-range theory in conscious forecasting based on future literacy. Research data were collected through purposive sampling using snowball technique and based on in-depth semi-structured interviews with experts in the field of futures, research and sports management. The number of participants in the study using the theoretical saturation index reached 14 people.In this study, data were coded and decomposed according to the field theory and with the construction approach. Instead of emphasizing the collection of facts and describing the actions, this approach emphasizes views, values, beliefs, feelings, defaults and ideologies of individuals. At the same time, interviews and receive feedback from interviewees during return to existing texts and documents, initial implications and codes were modified and modified. In this research, in all sampling process, three stages of free, communication and theoretical sampling stages were observed in the basis of the use of the construction approach of data theorem.Results: In this study, a multi-part model consisting of the main components of support processes, main processes, future images, future literacy and approaches was obtained. In this model, it was found that future literacy, which means encoding and decoding future images, can make conscious predictions about the future of public sports by using present-day potentials and existing processes.Conclusion: The arbitrary theory acknowledges that future literacy, which is an accessible skill based on human intrinsic capacity, can be based on current time potentials such as the main processes, such as identifying weak signals, surprises, macro trends, propulsion forces, uncertainties, design Strategic radar, based on environmental scanning and backup processes, such as inter-surface participation, key actor analysis, perspective, planning, entirely, cramps, and reengineering, make upcoming images; The upcoming literacy by decoding or coding these images based on the empowerment loop, which consists of four elements of awareness of the past and present, choosing and participating in the present and discovering in the coming time, provide information for different future.The existing system, beyond the conventional views in futures studies, can be a starting point for modeling informed predictions in sports. Manuscript profile -
Open Access Article
240 - A Hybrid Method for Long-Term Demand Forecasting in the Electrical Energy Supply Chain of Basic Metal Production Industries in the Presence of Incomplete Data
Sepehr Moalem Roya M.P. Ahari Ghazanfar Shahgholian Majid Moazzami Seyed Mohammad KazemiThe economic growth of any country has a lot to do with the infrastructure of the electrical energy supply chain and the ability to access it at low cost. Increasing the resilience of the electric energy supply chain in order to be able to respond to the real time deman MoreThe economic growth of any country has a lot to do with the infrastructure of the electrical energy supply chain and the ability to access it at low cost. Increasing the resilience of the electric energy supply chain in order to be able to respond to the real time demand of high-consumption and strategic consumers is a challenge that will not be possible without considering long-term demand forecasting and integrated development planning of this chain. This paper presents a long-term demand forecasting approach in the electrical energy supply chain of Isfahan's Espidan iron stone industries. This approach is a combination of wavelet transform, long short-term memory (LSTM) network and finally integrating the results with data-mining technique based on machine learning. The company studied in this research is one of the main suppliers of raw materials in the supply chain of basic metal production industries and one of the ten energy-intensive industries in the electrical energy supply chain of Isfahan province. The only information available from this company is the daily time series signal of the historical electrical energy demand of this industry in a period of 40 months. The data in the studied time series is interrupted so that only 50% of the data has a value and the remaining 50% is zero. This lack of data and the impossibility of access to supplementary data and effective features for forecasting has reduced the density of data and the possibility of long-term demand forecasting faces more problems than continuous time series. The used statistical analysis showed that the annual and seasonal data do not follow the normal distribution and have high distortion and heterogeneity. The proposed method and its results have been compared with other available approaches. The results of 10 iterations of extreme learning machine methods show that the RELM technique with a high confidence level of 95% is more effective than other machine learning methods and has more accurate results. Manuscript profile -
Open Access Article
241 - Analyzing Critical Discourse in Hafez’s Sonnet
Ahmad ZakeriToday, discourse is one of the prominent issues in various communities and is so important that it involves all political, philosophical and social worldviews. Linguists of recent era thrived to introduce the discourse as a linguistic component for attaining to the dept MoreToday, discourse is one of the prominent issues in various communities and is so important that it involves all political, philosophical and social worldviews. Linguists of recent era thrived to introduce the discourse as a linguistic component for attaining to the depth of hidden subjects in any discourse Discourse in formed by components such as power, worldview, literature and language. Western linguists sush asFerklaf, Yourgeness, Van Dick, and sociologists such as Fuko Smith, conducted many researches in the field of critical discourse and power. Consequently, the people interested in this component in Iran, by writing some books and papers about discourse has made their views This paper will analyze and investigate Hafez’s discourse in the critical view according to western linguistics; by analyzing the text, they interpret and explain the hidden layers of the meaning Manuscript profile -
Open Access Article
242 - The Concept of the Truth and Beauty of Mysticism and its Emergence in the Era of Islamic Architecture
KhosroZafarnavaei ZafarnavaeiThe beauty issue has been incorporated into the foundation of all human beings, so the recognition of beauty and the pursuit of beauty is rooted in our soul, and in fact, man needs to be in relation to beauty. Therefore, without the beauty of the soul, it remains in the MoreThe beauty issue has been incorporated into the foundation of all human beings, so the recognition of beauty and the pursuit of beauty is rooted in our soul, and in fact, man needs to be in relation to beauty. Therefore, without the beauty of the soul, it remains in the darkness and the violence of matter and in the domination of the quantities, the work of beauty with humanity is in fact attracting his attention. He is refreshed and meaningful in order to break down from quantity and to deal with qualities until his life. And in fact, the relationship between truth and meaning with beauty is explained in this way, because beauty is an expression of perfection or truth. In this article, we try to use the analytical and descriptive method and library studies to define the truth and beauty and the relation between two of the views of Islamic thinkers. Finally, the expression of these concepts and, in fact, the manifestation of content and truth in the body of Islamic architecture Check in. It is also possible to achieve perfection with care in a beautiful work, in addition to the fact that the sensation of human aesthetic is saturated. This is evident in the architecture of the Islamic era despite the long years of their creation due to the deep link between the artist and the eternal meanings and facts. Therefore, as far as the relationship between the three concepts (truth, beauty and art) goes further and deeper, a better and more useful understanding of beauty and perfection will arise, making the human a beautiful and humane art, as well as the ability to create works Beautiful and perfectionist, containing absolute truth. Manuscript profile -
Open Access Article
243 - An Overview of Modeling Weed Seedbank Dormancy and Germination
rahman khakzad Reza DeihimfardSeed dormancy is the failure of viable seeds to germinate in a specified period of time under optimal conditions for germination of non-dormant seeds and is one of the main mechanisms responsible for invasion and persistence of weeds in agricultural fields. Environmental MoreSeed dormancy is the failure of viable seeds to germinate in a specified period of time under optimal conditions for germination of non-dormant seeds and is one of the main mechanisms responsible for invasion and persistence of weeds in agricultural fields. Environmental factors such as temperature, moisture and chemicals affect the seed dormancy release and induction and consequently germination and seedling emergence patterns in the field. Thus, knowledge about seed dormancy and its relation with environmental factors is essential to predict the timing of germination and implementation of a rational strategy of weed management. The soil seed bank is the primary source of new infestations of annual weeds in crop production systems. Some annual weeds produce seeds that remain viable in the soil for many years, while others produce seeds that may be viable for only a single season. Seed persistence also may be influenced by depth of burial. Thus, knowledge of the length of seed persistence in the soil seed bank and periodicity of seedling emergence as influenced by the environment are of great importance for effective weed management. In this review, we present dormancy and germination models to predict timing and extent of emergence from weed seed bank. We hope that this paper will serve to give a general insight into modeling weed seedbank dormancy and germination and their use in weed science. Manuscript profile -
Open Access Article
244 - A Review of Weed Interference Models
rahman khakzad Mostafa Oviesi Reza DeihimfardWeeds represent a continuous problem in agricultural production due to their dynamic and resilient nature. Mathematical models offer a significant tool for understanding and predicting the crop yield losses incurred due to weed-crop interference. Weed-crop competition m MoreWeeds represent a continuous problem in agricultural production due to their dynamic and resilient nature. Mathematical models offer a significant tool for understanding and predicting the crop yield losses incurred due to weed-crop interference. Weed-crop competition models help to inform weed management decisions, both on a short-term basis to tackle the present weed population and in the long term to plan sustainable weed management strategies. Most competition studies are based on empirical models. Empirical functions are the most commonly used models, which provide information for weed threshold values. The limitations of such models are that they are based on statistical functions and usually do not consider biological insights for crop-weed interference. Crop-weed competition is a complex phenomenon, and to understand this, a detailed mechanistic model offers better insights than an empirical model. Mechanistic or explanatory models take into account all underlying processes or mechanisms and their dependence on each other with respect to time and external drivers. Competition models can be integrated within the framework of a decision support system (DSS). In this review, we present empirical and mechanistic models that are currently in use for studying crop-weed interference. Manuscript profile -
Open Access Article
245 - پیشبینی روند بازارهای مالی مبتنی بر مدلسازی مفاهیم نهفتهی اقتصادی در اسناد خبری
سعیده انبایی مجید وفایی جهان امین میلانی فرد سید رضا کامل -
Open Access Article
246 - Presenting a new model for rapid diagnosis of acute respiratory diseases using machine learning algorithms
Mehran Nezami Avaz Naghipour Behnam Safiri IranaghCorona virus, Severe Acute Respiratory virus and swine flu is a disease caused by acute respiratory syndrome. These viruses require advanced tools to identify dangerous mortality factors with high accuracy due to their immediate spread among humans. Machine learning met MoreCorona virus, Severe Acute Respiratory virus and swine flu is a disease caused by acute respiratory syndrome. These viruses require advanced tools to identify dangerous mortality factors with high accuracy due to their immediate spread among humans. Machine learning methods directly address this issue and are essential tools for understanding and guiding public health interventions. In this article, machine learning is used to investigate demographic and clinical significance. The investigated characteristics include age, gender, fever, countries and clinical details such as cough, shortness of breath, etc. Several machine learning algorithms have been implemented and applied on the collected data, the K-Nearest Neighbor algorithm works with the highest accuracy (more than 97%) to predict and select features that correctly represent the status of viruses. Manuscript profile -
Open Access Article
247 - واکاوی مفاهیم علمی و اعداد در رباعیات خیام، و ارتباط آن با چارچوب فکری او
اشکان گرشاسبی -
Open Access Article
248 - The Analysis of Forecasting the Monthly Trend According to Different Price Levels of Agricultural Crops (A Case Study Tomato & Potato )
Seyed Ehsan Zohoori reza moghaddasi einollah hesamiWhat is aimed in this research is to determine that are forecasts in years relatively high-price trend and low-price trend affected and smoothed according to the monthly potato and tomato prices? The analysis and forecasting of prices in harvesting seasons of two produc MoreWhat is aimed in this research is to determine that are forecasts in years relatively high-price trend and low-price trend affected and smoothed according to the monthly potato and tomato prices? The analysis and forecasting of prices in harvesting seasons of two products are implemented by “t” test and linear regression during 1996-2021. The results have showed significant forecasts for years with normal and high price levels meanwhile the research assumption of forecasting of the price trend has been approved more for potato in a high price level. The results of this research and similar cases can be used to forecast prices for production management of such crops, market regulation and consumers’ welfare of country in different seasons of the year. In case of extra supply with decreasing price level or lack of production with increasing price level one of approaches is to present template and compulsory cultivation in accordance with competitive advantages in provinces and different regions Manuscript profile -
Open Access Article
249 - Modeling the Amount of Required Energy and Kinetics of Lavender Drying Using Artificial Neural Network
Mohammad Younesi Alamooti Hamid Khafajeh Mohammad ZareinLavender with the scientific name Lavandula stricta Del is a perennial medicinal plant with a height of about half a meter that grows in different regions of Iran. Drying is one of the oldest methods of preserving materials. The use of neural networks can be used in the MoreLavender with the scientific name Lavandula stricta Del is a perennial medicinal plant with a height of about half a meter that grows in different regions of Iran. Drying is one of the oldest methods of preserving materials. The use of neural networks can be used in the design and selection of optimal working conditions and dryer control. In this study, various parameters of drying, evaluation of mathematical models to determine the best model, evaluation of different topologies of MLP artificial neural network to determine the best network for lavender plant with microwave dryer with power range of 100-1000 watts and The frequency of 2450 MHz is provided in four power levels of 300, 500, 700 and 900 watts. MLP artificial neural network was used to predict the relationship between drying kinetic parameters (moisture ratio and drying rate) and efficiency of energy consumption with changes in microwave power consumption using Statistica software. Among the fitted models, the Midili model was chosen as the best model according to R 2, χ 2 and RMSE criteria. Microwave power levels had an effect on drying time, with drying times of 3 minutes for 900 W power and 11 minutes for 300 W power. In order to predict drying kinetic parameters and energy consumption efficiency, MLP network with one input and three outputs was successfully used. The results generally showed that the MLP artificial neural network is a very powerful tool in predicting drying kinetic parameters and energy efficiency of lavender medicinal plant based on microwave power consumption values. Manuscript profile -
Open Access Article
250 - تحلیل و پیشبینی امواج گرمایی شهرهای منتخب شمال غرب ایران با استفاده از ریزگردان SDSM و شاخص بالدی
مجید رضایی بنفشه رقیه ملکی مرشت -
Open Access Article
251 - پیشبینی سیلاب رودخانه دینور با استفاده از شبکه عصبی مصنوعی
اعظم نجفی وفا محسن رضائی عارفی زیبا چمشه سفیدی -
Open Access Article
252 - بررسی کارائی مدل ریزمقیاس نمائی آماری (SDSM) در پیشبینی پارامترهای دمائی در سه اقلیم متفاوت (مطالعه موردی: مشهد و شیراز و رامسر)
مریم خسرویان غلامعباس فلاح قالهری علیرضا انتظاری رسول سروستانی -
Open Access Article
253 - The Effectiveness of Fordyce Cognitive-Behavioral Happiness Training on Women's Optimism and Marital Satisfaction
Zahra Shirin Javad Khalatbari Fardin FarmaniThe purpose of this study was to investigate the effectiveness of Fordyce cognitive-behavioral happiness training on the optimism and marital satisfaction of women. This study was a semi-experimental design with "pre-test and post-test design with control group". 30 wom MoreThe purpose of this study was to investigate the effectiveness of Fordyce cognitive-behavioral happiness training on the optimism and marital satisfaction of women. This study was a semi-experimental design with "pre-test and post-test design with control group". 30 women were randomly selected and assigned to two groups (Control and experimental group). Enrich Marital Satisfaction Questionnaire (1989) and Shirer and Carver Optimism Questionnaire (1994) were used to collect data. Training intervention was conducted for the experimental group for 8 sessions of 2 hours. At the end, the results were analyzed with covariance analysis method. The findings of this study showed that cognitive-behavioral happiness training by Fordyce method is effective on two variables of optimism and marital satisfaction, and there was a significant difference between the experimental group and the control group. Considering the findings of this study, this method can be used to reduce couples conflicts and increase the quality of their relationships. Manuscript profile -
Open Access Article
254 - The Comparison Of Death Anxiety, Optimism And Sense Of Humor Among Female Nurses
Farah Naderi سعید Bakhtiar poor مینا ShokouhiIn the current established study the comparison of optimism, sense of humor and death anxiety among nurses in different wards of Ahwaz Golestan Hospital was proceeded. Statistical universe included all the female nurses of Ahwaz Golestan Hospital (240 nurses) being in d MoreIn the current established study the comparison of optimism, sense of humor and death anxiety among nurses in different wards of Ahwaz Golestan Hospital was proceeded. Statistical universe included all the female nurses of Ahwaz Golestan Hospital (240 nurses) being in duty for the year 1389 in seven different wards: The General Emergency, Intensive Care Unit, Nephrology(kidney Diseases), Surgery, Psychiatry, Internal Operating Room and pediatrics(Children) wards. The sample encompassed 200 female nurses whom were selected randomly via simple sampling procedure. Collelt-Lester Fear of Death Scale (Cl-FODS), Attribution Styles Questionnaire (ASQ) and the Sense of Humor Scale (Martin and Lefcourt) were responded by the subjects as data source. The research was designed as ex-post facto. Data analysis through multivariate analysis of variance (MANOVA) and Sheffe post hoc test were implemented. The findings revealed that nurses in hospital various wards differed significantly in terms of death anxiety but no any significant difference was observed with respect to other variables. Manuscript profile -
Open Access Article
255 - The Relationship Of Secure Attachment Style, Optimism and Social Support with Life Satisfaction in Female Students of Shahid Chamran University
اکرم Nazari Chegani ناصر Behrozi مهناز Mehrabizade Honarmand اسماعیل Hashmi Shikh ShabaniThe aim of this research was to examine the relationship between secure attachment style, optilmism and social support with life satisfaction in female undergraduate students of Shahid ChamranUniversity. The sample included 300 individuals that were selected through mul MoreThe aim of this research was to examine the relationship between secure attachment style, optilmism and social support with life satisfaction in female undergraduate students of Shahid ChamranUniversity. The sample included 300 individuals that were selected through multistage randomsampling among all female undergraduate students of Shahid Chamran University. Simpson Adullat Attachment Inventory (AAI), Life Orientation Test-Reviseved (LOT-R; Scheier, Carver andBridge), Phlips Social Support Inventory (PSSI), Beck Depression Inventory (BDI) and Satisfacltion with Life Scale (SWLS; Ryff, Lee, Essex and Schmutte) were used for data collecting. Theresearch was designed as correlation type. Results of data analysis by using Pearson correlationcoefficient and multivariable regression showed that there was significant positive relation betweensecure attachment style, optimism and social support with life satisfaction. Finally, the results alsoindicated that optimism, social support, avoidant insecure attachment and secure attachment, relspectively, were the best predictors of life satisfaction. Manuscript profile -
Open Access Article
256 - The Relationship of Religious Beliefs, and Resilience with Optimism In Female High School Students
مرضیه Nasir فرح NaderiThis study examined the relationship between religious beliefs, and resiliency with optimism of students. The statistical population consisted of high school students in Dezful city, of which 300 students were randomly selected via cluster sampling procedure. Tools used MoreThis study examined the relationship between religious beliefs, and resiliency with optimism of students. The statistical population consisted of high school students in Dezful city, of which 300 students were randomly selected via cluster sampling procedure. Tools used in this study included Questionnaire Of Religious Beliefs, Conner and Davidson Resiliency Scale (CD-RISC), and the Optimism Questionnaire (ASQ). All of the scales had acceptable validity and reliability. The research was a correlation study. To analyze data multiple regression method was used. Results showed that there existed significant positive relationship religious beliefs and resiliency with optimism. The result of multiple regression analysis also revealed that religious beliefs and resiliency are respectively significantly predicted optimism. Manuscript profile -
Open Access Article
257 - Pathology Of Lesbianism
محسن Doostkam مهناز Mehrabi-zadeh Honarmand S. A. Ghanavati سپیده Pour-HeidarHuman sexual orientation has strong effect on determining sexual schemas, sexual partners and behaviors, so it is important to study it from a multiple perspectives. Growing sexual distortions in the West and its effects on policy, economy and etc. is an issue that coul MoreHuman sexual orientation has strong effect on determining sexual schemas, sexual partners and behaviors, so it is important to study it from a multiple perspectives. Growing sexual distortions in the West and its effects on policy, economy and etc. is an issue that could not be ignored. The role of women is substantial, especially in the western culture that beholds them as a commercial object. The Western governments use any means to induce their goals, even in other cultures especially Islamic ones. In the current article we investigated theories about lesbianism in women from a multiple perspectives including biological, cultural and psychosocial types. Also we have examined their strength. One of these theories is feminism – lesbianism theory which has basic role in shaping and inducing false ideas about women and lesbianism in women into culture. Manuscript profile -
Open Access Article
258 - مدلسازی هیدروگراف جریان با استفاده از GIS و مدل هیدرولوژیکی توزیعی در حوزه دینور کرخه
مریم آذین‏ مهر عبدالرضا بهره‏ مند آتنا کبیردر این مقاله اساس مدل‏ سازی در حوزه بصورت تقسیم‏‏ بندی آن بصورت شبکه‏ ای می ‏باشد، به ­طوری که هر سلول یک تابع پاسخ مستقل و منحصر به­ فردی نسبت به سایر سلول‏ ها دارد. از مجموع پاسخ‏ های جریان سلول‏ ها، هیدروگراف جریان از سطح حوزه Moreدر این مقاله اساس مدل‏ سازی در حوزه بصورت تقسیم‏‏ بندی آن بصورت شبکه‏ ای می ‏باشد، به ­طوری که هر سلول یک تابع پاسخ مستقل و منحصر به­ فردی نسبت به سایر سلول‏ ها دارد. از مجموع پاسخ‏ های جریان سلول‏ ها، هیدروگراف جریان از سطح حوزه حاصل می ‏شود. روش ارائه شده، پیش ‏بینی هیدروگراف جریان حوزه رودخانه با استفاده از مدل هیدرولوژیکی WetSpa است. WetSpa یک مدل هیدرولوژیکی- توزیعی بر پایه GIS می‏باشد که در مقیاس حوزه عمل کرده و برای پیش‏ بینی سیلاب و مدیریت حوزه آبخیز توسعه یافته است. مدل فیزیکی بوده و قادراست فرایندهای هیدرولوژیکی بارش، ذوب برف، ذخیره برگابی، ذخیره چالابی، رواناب سطحی، نفوذپذیری، تبخیر و تعرق، نفوذ عمقی، جریان زیر سطحی، جریان آب زیر زمینی و... را به طور پیوسته در زمان و مکان شبیه ‏سازی نموده و تعادل آب و انرژی را در هر سلول رستری برقرار نماید. مدل از لایه های توپوگرافی، کاربری و خاک و همچنین آمار هواشناسی روزانه برای پیش‏ بینی هیدروگراف ‏های سیل و توزیع مکانی پارامترهای هیدرولوژیکی حوزه استفاده می ‏نماید. نقشه‏ های رقومی توپوگرافی، کاربری اراضی و بافت خاک سه نقشه اصلی مدل بوده که در قالب GIS و با ابعاد سلولی100 ×100 متر به مدل وارد شدند. مدل با 76 ماه آمار هیدرومتئورولوژیکی اندازه‏گیری شده در حوزه دینور کرخه در کرمانشاه به کار برده شد. نتایج شبیه‏ سازی حاکی از تطابق خوب بین هیدروگراف ‏های شبیه‏ سازی و مشاهده‏ای است به طوریکه مدل قادر است هیدروگراف ‏های روزانه را با دقت خوب و بر اساس معیار ناش-ساتکلیف دوره واسنجی و کلینگ- گوپتا دوره اعتبارسنجی به ترتیب 66 درصد و 72 درصد پیش ‏بینی نماید. Manuscript profile -
Open Access Article
259 - ارزیابی رسوبگذاری در مخزن سد مسجد سلیمان با مدل ریاضی GSTARS-3
رضا تاج مهر هوشنگ حسونی زاده سمانه عبدویسانتقال و انباشت رسوبات در سدهای مخزنی باعث تقلیل حجم و عمر مفید مخازن ذخیره آب می شود. هدف از این مقاله بررسی میزان اثر پارامترهای موثر در مدل رسوب گذاری وپیش بینی میزان رسوب در مخزن سد مسجد سلیمان می باشد. لذا از مدل شبه دو بعدی Gstarsاستفاده شد. نتایج نشان داد که م Moreانتقال و انباشت رسوبات در سدهای مخزنی باعث تقلیل حجم و عمر مفید مخازن ذخیره آب می شود. هدف از این مقاله بررسی میزان اثر پارامترهای موثر در مدل رسوب گذاری وپیش بینی میزان رسوب در مخزن سد مسجد سلیمان می باشد. لذا از مدل شبه دو بعدی Gstarsاستفاده شد. نتایج نشان داد که مدل نسبت به پارامتر الگوی ترسیب و معادله انتقال رسوب بیشترین حساسیت را نشان می­ دهد. همچنین کالیبراسیون مدل با استفاده از آمار سیلاب­ های لحظه­ای دارای حساسیت کمتری نسبت به آمار روزانه می ­باشد. میزان خطای قابل اغماض میان مقادیر مشاهده ای و نتایج محاسبه ها دو درصد بود که نشان دهنده آنست که مدل ریاضی Gstarsجهت استفاده در تخمین میزان و نحوه توزیع رسوب مناسب است. در نهایت کاهش حجم سالیانه مخزن 6/1 درصد برآورد شد که مقدار مشاهده ای آن برابر 1/1 درصد است. Manuscript profile -
Open Access Article
260 - استفاده از روشهای شبکه عصبی موجکی و سیستم استنتاج فازی عصبی تطبیقی در پیشبینی بارش ماهانه
اباذر سلگی حیدر زارعی بهداد فلامرزیپیش بینی بارش به دلیل ماهیت تصادفی آن در مکان و زمان همواره با مشکلات بسیاری مواجه بوده است و این عدم قطعیت از اعتبار بسیاری از مدل های پیش بینی می کاهد. امروزه شبکه های غیرخطی به عنوان یکی از سیستم های هوشمند در پیش بینی یک چنین پدیده های پیچیده ای بسیار مورد استفاده ق Moreپیش بینی بارش به دلیل ماهیت تصادفی آن در مکان و زمان همواره با مشکلات بسیاری مواجه بوده است و این عدم قطعیت از اعتبار بسیاری از مدل های پیش بینی می کاهد. امروزه شبکه های غیرخطی به عنوان یکی از سیستم های هوشمند در پیش بینی یک چنین پدیده های پیچیده ای بسیار مورد استفاده قرار می گیرند. یکی از روش هایی که در سال های اخیر در زمینه هیدرولوژی مورد توجه قرار گرفته است، استفاده از تبدیل موجک به عنوان روشی نوین و مؤثر در زمینه آنالیز سیگنال ها و سری های زمانی است. در پژوهش حاضر، تجزیه و تحلیل موجک به صورت ترکیب با شبکه عصبی مصنوعی و مقایسه با سیستم استنتاج فازی- عصبی تطبیقی برای پیش بینی بارش ایستگاه وراینه در شهرستان نهاوند انجام شد. برای این منظور، سری زمانی اصلی با استفاده از تئوری موجک به چندین زیرسیگنال زمانی تجزیه شد، پس از آن این زیرسیگنال ها به عنوان داده های ورودی به شبکه عصبی مصنوعی برای پیش بینی بارش ماهانه استفاده شد. نتایج به دست آمده نشان داد که مدل ترکیبی موجک- شبکه عصبی عملکرد بهتری نسبت به مدل سیستم استنتاج فازی- عصبی تطبیقی دارد و می تواند برای پیش بینی بارش کوتاه مدت و بلند مدت استفاده شود. همچنین نتایج نشان داد که مدل ترکیبی موجک- شبکه عصبی در برآورد نقاط حدی به خوبی عمل می کند. Manuscript profile -
Open Access Article
261 - تغییرات شوری اعماق خاک در اثر آبیاری با آب شور
وحید یزدانی سپیده یکه باش محمد سلطانیاین تحقیق به منظور بررسی تاثیر شوری آب آبیاری بر کیفیت خاک در سطح و اعماق انجام گرفت. در این تحقیق از نسبت­های مختلف سنگ نمک طبیعی و آب چاه با دبی 35 لیتر در ثانیه (در مختصات ً5/39 َ27 º59 و ً2/39 َ27 º36) به منظور ایجاد شوری­های متفاوت در Moreاین تحقیق به منظور بررسی تاثیر شوری آب آبیاری بر کیفیت خاک در سطح و اعماق انجام گرفت. در این تحقیق از نسبت­های مختلف سنگ نمک طبیعی و آب چاه با دبی 35 لیتر در ثانیه (در مختصات ً5/39 َ27 º59 و ً2/39 َ27 º36) به منظور ایجاد شوری­های متفاوت در شرایط کشت کلزا استفاده شد. در شرایط ماندگار، در یک غلظت مشخص از آب آبیاری، توزیع متفاوت در جذب آب سبب توزیع متفاوت شوری در خاک می­شود. بر این اساس، از معادلات تابع جذب آب نمایی، ذوزنقه­ای و الگوی جذب جهت بررسی تغییرات شوری استفاده شد. نتایج نشان داد با افزایش زمان بعد از کاشت و اعمال تیمار­های مختلف آبیاری، مقدار شوری عصاره اشباع خاک در اعماق مختلف خاک افزایش می­یابد. در 3 تاریخ اولیه مقدار تفاوت در EC عصاره اشباع خاک خیلی زیاد نیست و در تاریخ 4 و 5 نمونه‎برداری (یعنی 102 و 118 روز بعد از کشت کلزا) مقدار تفاوت­ها بیشتر می­شود. دلیل تفاوت کم در تاریخ‎های 56، 71 و 87 روز بعد از کشت کلزا، وجود بارش در این مدت می­باشد. در 71 روز بعد از کشت کلزا مقدار EC عصاره اشباع در اغلب تیمار­ها کاهش داشت و از روند افزایشی پیروی نمی­کرد که دلیل آن وقوع بارش در بازه اول الی 15 خرداد بود؛ که باعث آب‎شویی املاح شده و EC عصاره اشباع خاک کاهش یافته است. البته باید اشاره داشت که در تیمار I4 چنین روندی مشاهده نمی­گردد. زیرا کم‎آبیاری شدید در این تیمار باعث تجمع املاح در سطح خاک شده است که بارش­ها تنها سطح خاک را آب‎شویی نموده و املاح را به اعماق پایین‎تر منتقل کرده است. نتایج نشان داد که مدل ذوزنقه­ای قادر به پیش‎بینی شوری عصاره اشباع خاک نمی­باشد. این روش شوری عصاره اشباع خاک را بسیار بیشتر از واقعیت برآورد می­کند و نتایج آن تنها در شوری 5/0 دسی زیمنس بر متر تاحدودی قابل قبول است. در مقابل، نتایج دو مدل دیگر یعنی مدل نمایی و مدل تابع جذب، نتایج مناسب‎تری را ارائه دادند. مدل نمایی در این سه سطح آبیاری دارای دقت قابل قبول­تری نسبت به مدل تابع جذب بود. Manuscript profile -
Open Access Article
262 - پیش بینی و آنالیز حساسیت تبخیر ماهانه از مخزن سد سیاه بیشه با استفاده از شبکههای عصبی مصنوعی در ترکیب با الگوریتم ژنتیک
آزاده محمدیان شوئیلی حسن فتحیان مهدی اسدی لورفرآیند تبخیر، یکی از مؤلفههای اصلی چرخه آب در طبیعت است که نقش اساسی در مطالعات کشاورزی، هیدرولوژی و هواشناسی، بهره برداری از مخازن، طراحی سیستمهای آبیاری و زهکشی، زمان بندی آبیاری و مدیریت منابع آب ایفا میکند. روشهای زیادی از جمله روشهای بیلان آب، تبخیر از تشت و ر Moreفرآیند تبخیر، یکی از مؤلفههای اصلی چرخه آب در طبیعت است که نقش اساسی در مطالعات کشاورزی، هیدرولوژی و هواشناسی، بهره برداری از مخازن، طراحی سیستمهای آبیاری و زهکشی، زمان بندی آبیاری و مدیریت منابع آب ایفا میکند. روشهای زیادی از جمله روشهای بیلان آب، تبخیر از تشت و روشهای تجربی برای تخمین تبخیر از سطح آزاد، ارائه شده است که هر کدام از این روشها، با محدودیت و خطای اندازه گیری توأم میباشد. امروزه تکنیک جدید استفاده از شبکههای عصبی مصنوعی که مبتنی بر هوش مصنوعی میباشد کاربرد گسترده ای در زمینههای مختلف علمی به ویژه مهندسی آب پیدا کرده است. در این تحقیق با استفاده از مدل شبکه عصبی مصنوعی پرسپترون چند لایه(MLP)، شبکه تابع پایه شعاعی (RBF) و شبکه پیش رونده(FF)،میزان تبخیر ماهانه از مخزن سد سیاه بیشه تا 3 ماه آیندهپیش بینی شد. برای تعیین متغیرهای ورودی مؤثر در مدلهای شبکه عصبی مصنوعی و تعداد نرونها در لایه میانی هر یک از مدلها، از قابلیت بهینه سازی الگوریتم ژنتیک استفاده شد. نتایج نشان میدهد که ضریب همبستگی بین مقادیر اندازه گیری شده و محاسبه شده با مدلهای RBF ، MLPو FFدر برآورد و پیش بینی تبخیر ماهانه از مخزن سد سیاه بیشه به ترتیب برابر با 92/0، 90/0 و 88/0 میباشد. بنابراین مدل RBF از دقت بیشتری نسبت به دو مدل MLP وFFدر برآورد و پیش بینی میزان تبخیر ماهانه از مخزن سد، برخوردار میباشد. نتایج حاصل از آنالیز حساسیت نشان میدهد که تبخیر ماهانه از مخزن سد تا 3 ماه آینده به ترتیب نسبت به زمان وقوع تبخیر بر حسب ماه، فشار هوا در سطح زمین در 1 ، 3 و2 ماه قبل، سرعت باد در سطح 1000 میلی بار در 3 و 2 ماه قبل و دمای هوا در سطح 300 میلی بار در زمان حال بیشترین حساسیت را دارد. Manuscript profile -
Open Access Article
263 - Improve the accuracy of project construction forecasts by integrating managed value management with quantitative predictive methods in time series. Case study: Construction projects at AzarAB Company Arak
Mehrdad Khazenchin Amir abbas ShojaieIn this research, two projects were considered during the construction phase of Azar AB Company to predict construction costs and actual costs of these projects were calculated after data collection, then six regression models were presented in four time periods for eac MoreIn this research, two projects were considered during the construction phase of Azar AB Company to predict construction costs and actual costs of these projects were calculated after data collection, then six regression models were presented in four time periods for each project and then The average model error for each project was calculated in four periods to determine the final and acceptable model for each project. The results showed that models 2 and 3 percent have lower and acceptable errors than other models. The existence of effective modules in models as well as in terms of the nature of projects, we conclude that Model No. 3 predicts the future costs of projects with a reasonable degree of certainty. In sum, we will select Model No. 3 as the top model to predict the future costs of the projects in question. However, we recall that for each project, depending on its nature, another particular equation may provide more accurate predictions. But in general it can be said that regression models are used to predict the costs of different periods The project is applicable to its nature. Manuscript profile -
Open Access Article
264 - Determining the optimal forecasting combination of the four-level supply chain to minimize the bullwhip effect
Maryam Daneshmand-Mehr Marzban Najafi Ramin SadeghianBullwhip effect that occurs in the chain, leads to inefficiencies such as excess inventory and overdue orders during the chain. These problems can be reduced by appropriate predictions. Forecasting must be done in all levels of a supply chain. This paper addresses the p MoreBullwhip effect that occurs in the chain, leads to inefficiencies such as excess inventory and overdue orders during the chain. These problems can be reduced by appropriate predictions. Forecasting must be done in all levels of a supply chain. This paper addresses the problem of optimal combination of forecasting to reduce the bullwhip effect in the four-level supply chain. For this purpose, a four-level supply chain is considered. One of the methods such as moving average, exponential smoothing, linear regression and multilayer perceptron artificial neural network can be considered for predicting in each level. First, the desired supply chain is simulated for this means. The different combinations of aforementioned forecasting methods are calculated. Then a combination of forecasting methods according to minimized bullwhip effects is selected. Finally, the results are analyzed by variance analysis model. Two combinations have the lowest bullwhip effects. Moving average, neural networks, exponential smoothing and linear regression for levels: retailer, wholesaler, manufacturer and supplier respectively as an answer and the other is: moving averages, exponential smoothing, neural network and linear regression in the same mentioned levels and other combinations have less utility. Manuscript profile -
Open Access Article
265 - Identifying the influencing factors in customer churn of Kurdistan Telecommunications Company and presenting models for predicting churn using machine learning algorithms
vida sadeghi Anvar Bahrampour Seyed Ali HosseiniThe main sources of income and assets are important for any organization. With this view, companies have started to do more to maintain health. Since in many companies the cost of acquiring a new customer is much higher than actual customer satisfaction, customer churn MoreThe main sources of income and assets are important for any organization. With this view, companies have started to do more to maintain health. Since in many companies the cost of acquiring a new customer is much higher than actual customer satisfaction, customer churn has become the main area of evaluation for these companies. Client-facing companies, including those active in the technology industry, are facing a major challenge due to customer attrition. With the rapid development of the telecommunications industry, dropout prediction becomes one of the main activities in gaining a competitive advantage in the market. Predicting customer churn allows operators a period of time to remediate and implement a series of preventative measures before customers migrate to other operators. In this research, a decision support system for predicting and estimating the churn of customers of Kurdistan Telecommunication Company (with 52,900 subscribers) with different data-mining and machine methods (including simple linear regression (SLR), multiple linear regression (MLR). Polynomial regression. (PR), logistic regression, artificial neural networks, Adabust and random forest) are presented. The results of the evaluations carried out on the data set of the Kurdistan Province Telecommunication Company, the high performance of artificial neural network methods with 99.9% accuracy, Adabust with 99.9% accuracy, 100% accuracy and random forest It shows 100% with accuracy. Manuscript profile -
Open Access Article
266 - A Learning Automaton Based Algorithm for Bankruptcy Prediction of Acceptable Firms within Power and Energy Exchange
Seyed Mahdi Mazhari Hassan Monsef Hooman MirzaeiIn today's world, insurance of productive capital investment and reducing economic risk causes more fundraising and therefore the greatest economic boom cycle. One way to arrive capital investment security is to predict bankruptcy of a business unit. As the Iranian powe MoreIn today's world, insurance of productive capital investment and reducing economic risk causes more fundraising and therefore the greatest economic boom cycle. One way to arrive capital investment security is to predict bankruptcy of a business unit. As the Iranian power and energy stock is going to start working by 2012, providing suitable bits of advice to investors would be a priority. This paper proposes a new solution approach for bankruptcy prediction of the Iranian power and energy industries. To do so, an evolutionary algorithm premised on Learning Automata is employed and adapted to the problem. Two sets of firms related to power and energy industries that are listed on the Tehran Stock Exchange (TSE) are selected as the training and test data, respectively. The developed algorithm is conducted on both train and test data, and the efficiency of the proposed method is evaluated via several scenarios. It was practically seen in simulations that the learning automata-based algorithm could achieve an accuracy of 91% and 88% over the train and test data, respectively. Besides these, the same data sets are also conducted by other methods such as MDA and Logit, and the obtained results are compared with reality. The yielded results prove the accuracy as well as the efficiency of the proposed solution technique Manuscript profile -
Open Access Article
267 - Improving Inventory Performance with Clustering based Demand Forecasts
Yaser TaghinezhadProper management and better control of inventory of food items are one of the most important and important goals of food store managers. In this study, we try to provide knowledge of customer segmentation based on various characteristics as inputs in predicting retail MoreProper management and better control of inventory of food items are one of the most important and important goals of food store managers. In this study, we try to provide knowledge of customer segmentation based on various characteristics as inputs in predicting retail demand. The purpose of this paper is to provide a prediction model for retailers based on customer clustering to improve inventory performance. Customer clustering with the genetic algorithm is performed in MATLAB R2016a software. The proposed model is used to predict the demand for five items of supermarket goods in Gorgan. In this paper, the predictions of ARIMA, ARIMA, MLP, and GMDH neural networks are used to predict. Modeling of these models has been done in MATLAB software. The results showed that the GMDH neural network with the clustering of customers had the least predictive error. The model predicted by the inventory control policy reduces the number of days that the shortage faces and increases the level of service to the customer. Retailers can use the proposed model to predict the demand for various items to improve inventory performance and profitability of operations. Manuscript profile -
Open Access Article
268 - The Structural Modeling of the Relationship between Teaching Approaches and Academic Achievement Goals: Explaining the Mediating Role of Students' Academic Optimismtle
mohammad hajizad The aim of this study was to investigate the structural modeling of the relationship between teaching approaches and goals of academic achievement with the mediating role of students' academic optimism. This is an applied research and descriptive corr More The aim of this study was to investigate the structural modeling of the relationship between teaching approaches and goals of academic achievement with the mediating role of students' academic optimism. This is an applied research and descriptive correlation method of path analysis. The statistical population of all female high school students in Neka city was 2000 students in the academic year 2021-2022 They were studying. Sample size According to Krejcie and Morgan table, 317 students were selected by stratified random sampling method based on educational background. Data collection tools include standard questionnaires Kadivar teachers' teaching approaches, Migli's achievement goals and academic optimism by Ghasemi. The supervisor and the consultant due to their standardization approved the face validity of the questionnaires. The reliability of the questionnaires was obtained through Cronbach's alpha coefficient for Kadivar (1399) teaching approaches 89%, Migli (2000) achievement goals (81) and Ghasemi (1397) 86% academic optimism. Data were analyzed using descriptive statistics (frequency tables, mean and standard deviation) and inferential statistics (Pearson correlation coefficient and SEM structural equations by SPSS22 software) and Smart PLS). Data analysis showed that there is a positive and significant relationship between the components of teaching approaches and achievement goals in students. There is a positive and significant relationship between the components of teaching approaches and academic optimism in students. There is a positive and significant relationship between the components of academic optimism with achievement goals in students and also other research findings showed that there is a positive and significant relationship between teaching approaches and achievement goals with the mediating role of academic optimism in students. Manuscript profile -
Open Access Article
269 - Structural Equations’ Modeling Relationship between Dimensions of Psychological Capital and mental Hardiness of Employees of Bojnourd Municipality
hajar elahi behrang esmaeili shadThe purpose of the study is to consider the relationship between the dimensions of psychological capital and mental hardiness. The research method is descriptive and correlational. The statistical population consisted of 220 employees in Bojnourd municipality that accor MoreThe purpose of the study is to consider the relationship between the dimensions of psychological capital and mental hardiness. The research method is descriptive and correlational. The statistical population consisted of 220 employees in Bojnourd municipality that according to the Kerjesi-Morgan (1970) table, 155 person were selected by simple random method. The data were collected by questionnaires. Lutans(2007) psychological Capital and hardiness Long and Gollet (1989) questionnaire which their reliability was estimated by Cronbach's alpha (89%) and (84%) and the validity were formal and content type.. The result showed with regard to the amount of path coefficient obtained, 72% and 5/73%, there is a significant relationship between psychological capital and mental hardiness. The coefficients of path between self-efficacy and subjective hardiness of employees were 49% and t-statistic for this coefficient was 6/67, which showed that there is a positive and significant relationship between self-efficacy and mental hardiness. The path coefficient between employees' mental hardiness and hopefulness is 64%. t-statistic for this relationship (6/97) showed that there is a significant and positive relationship between hope and mental hardiness. The amount of path coefficient among the resiliency and mental hardiness of the staff (50%) and the t-value for this coefficient ( 5.50 )showed that there were a positive and significant relationship between the resiliency and mental hardiness of the staff. the path coefficient of relationship between optimism and subjective hardiness of employees ( 73%) and the value of t (7/17) showed there is positive relationship between optimism and mental hardiness of employees. Manuscript profile -
Open Access Article
270 - Effectiveness of mindfulness training on components of Students' academic optimism (social confidence, academic emphasis and identity sense)
Fereshteh Hashemi Fariborz Dortaj Noorali Farrokhi Bita NasrollahiPresent study aimed to determine the effectiveness of mindfulness training on components of students' academic optimism (social confidence, academic emphasis and identity sense). This research was quasi-experimental with a pretest-posttest design with experimental and c MorePresent study aimed to determine the effectiveness of mindfulness training on components of students' academic optimism (social confidence, academic emphasis and identity sense). This research was quasi-experimental with a pretest-posttest design with experimental and control groups. Research population was eight grade students in one district of Tehran city in 2016-17 academic years. Totally 40 people were selected by random cluster sampling method and assigned in two equal experimental and control groups. Experimental group trained 8 sessions of 75 minutes the mindfulness program and the control group received no training. Research tool was academic optimism (Tschannen-Moran and et al, 2013). Data were analyzed by tests of t and multivariate analysis of covariance in SPSS version 20 software. The findings showed that in the pretest the experimental and control groups there was no significant difference in terms of components of academic optimism means social confidence, academic emphasis and identity sense (P>0/05), but in the posttest there was significant difference in terms of components of academic optimism (P<0/001). That's it mindfulness training led to increase components of academic optimism means social confidence, academic emphasis and identity (P<0/001). Based on the results, it can be said that mindfulness training led to increases students' academic optimism and its components. Manuscript profile -
Open Access Article
271 - investigated the prediction of social problem solving styles based on the dimensions of psychological capital in students
majid saffarinia mohsen zali zadehThe aim of this study was to investigate the predictions of social problem solving styles based on the dimensions of psychological capital in students. The present study was a correlational section The statistical population of this study consisted of students studying MoreThe aim of this study was to investigate the predictions of social problem solving styles based on the dimensions of psychological capital in students. The present study was a correlational section The statistical population of this study consisted of students studying at Shahid Chamran University in the first semester of the 2016-2017academic year. 500 people were selected using multi-stage cluster random sampling. Data collection through Lutans et al.'s psychological capital scales, (2007) with Khosroshahi et al.'s (2012) spring normative normativeness, overall reliability scale based on Cronbach's alpha of 0.85, and Dezurilla et al (2002) social problem solving styles, With informational standardization,mokhberi et al. (2010), the overall reliability of the scale based on Cronbach's alpha coefficient was reported to be 0.85. Data were analyzed using Pearson correlation coefficient and stepwise regression in SPSS-18 software. The findings showed a significant positive relationship between positive orientation to the problem and logical problem solving with the variables of self-efficacy, hope, resilience and optimism. The impulsive / careless style had a significant negative relationship with self-efficacy, and the avoidant style had a significant negative relationship with self-efficacy, hope, optimism. Also, in order of positive orientation to the issue of 32 /. Percentage, negative orientation 31/. Percentage, Problem Solving Style 47/. Percentage, impulsive / careless style 22 /. Percentage, avoidance style 37/. They were able to predict changes in students' psychological capital (P <0.05). It can be said that people with higher psychological capital are more able to solve social problem Manuscript profile -
Open Access Article
272 - Predictors of opium in adolescents: individual, family and social factors
Hasan Rezaei jamaloei Shima Mansourifar Mahdi taheri Sajad AminimaneshConsidering the risks of opium use among adolescents and Need to identify the components and dimensions of these behaviors In order to design appropriate and effective interventions, the aim of this study was conducted to determine the predictors of Opium Use (Individua MoreConsidering the risks of opium use among adolescents and Need to identify the components and dimensions of these behaviors In order to design appropriate and effective interventions, the aim of this study was conducted to determine the predictors of Opium Use (Individual, family and social) among students. The research method was descriptive correlational. The statistical population of the study was all male high school students in Isfahan in 1397, who were selected using the cluster random sampling method of 201 people and were evaluated by the drug consumption profile and the drug status status questionnaire. The research instruments included the standard questionnaire of drug consumption profile (Mohammadkhani, 2007) and the questionnaire on the status of drug use (Mohammadkhani, 2006). Data analysis results were performed using Pearson correlation coefficient and stepwise regression. The results correlation coefficient showed that were significant positive correlation betweenOpium Use in a lifetime with components Attitudes toward drug use, hopelessness, sensation seeking, impulsivity, family conflict, parental attitudes to drugs, family monitoring, irregularities social environment, a sense of commitment to school and school psychosocial environment of profile of risk use drug (p<./05) .Also the resultsStepwise regression analysis showed that Components of attitudes to drug usepredictive variance Opium Use in a lifetime with components to explain the 47 percent. Also attitudes toward drug use and hopelessness 17 percent of variance the opium use in the past month and 17 percent of variance the opium use in the past 12 monthpredictive and explain. According to the resultscan be saidopium Use by adolescents is a multi-factor and multi-level and Major factors determining there are At multiple levels: individual, social and family that Should for intervention, prevention, control opium are be considered. Manuscript profile -
Open Access Article
273 - Development of a causal model of academic satisfaction based on academic self-confidence and academic optimism mediated by metacognitive strategies and its effectiveness on academic Self-actualization of first year high school male students in Hamadan
Gholamreza Ebrahimzadeh Houshang Jadidi Yahya Yarahmadi Omid MoradiThe aim of this study was to investigate the development of a causal model of academic satisfaction based on academic self-confidence and academic optimism through the mediation of metacognitive strategies and its effectiveness on academic Self-actualization of male hig MoreThe aim of this study was to investigate the development of a causal model of academic satisfaction based on academic self-confidence and academic optimism through the mediation of metacognitive strategies and its effectiveness on academic Self-actualization of male high school students in Hamadan. This research was conducted in two stages. The research method was descriptive-correlational in the first stage. The second stage was a quasi-experimental research method with a pretest-posttest design with a control group. Using the available sampling method, in the first study, 338 people were selected as the statistical sample size based on Morgan table, and in the second study, 30 people (15 people in the experimental group and 15 people in the control group) were selected as the statistical sample size. ) were chosen. The experimental group received 10 sessions of 90 minutes and the control group did not receive training. Research tools in this study include the standard questionnaire of student satisfaction (Lent, 2017), the questionnaire of academic self-confidence (Azadi, 1394), the questionnaire of academic optimism (Schennemoran et al., 2018), the questionnaire of academic Self-actualization (Silson and Salasi, 2003) and The questionnaire was metacognitive strategies (Karami, 2015). In this study, structural equation modeling and analysis of covariance were used to analyze the data. It should be noted that these analyzes were performed with the help of SPSS and AMOS software version 23 at the error level of 0.05. Findings showed that academic self-confidence and academic optimism have a significant causal relationship with metacognitive strategies and academic satisfaction. It was also found that the causal relationship between metacognitive strategies and academic satisfaction is significant. Finally, the results confirmed the mediating role of metacognitive strategies in the relationship between these variables. The results also showed that the educational program based on academic satisfaction is effective on students' academic Self-actualization. Manuscript profile -
Open Access Article
274 - Predicting social development based on social trust and optimism in faculty members
SeyedNematollah Kamali Kar Salari Farshideh ZameniThe aim of this research was predicting social development based on social trust and optimism in faculty members. This study in terms of purpose was applied and in terms of implementation was a cross-sectional correlational. The research population was faculty members o MoreThe aim of this research was predicting social development based on social trust and optimism in faculty members. This study in terms of purpose was applied and in terms of implementation was a cross-sectional correlational. The research population was faculty members of Islamic Azad Universities of Mazandaran province in 2020 year with number of 1487 people. The sample size based on Cochran's formula was estimated 305 people who were selected by multi-stage cluster sampling method. The research tools were questionnaires of researcher-made social development, Afshani and Shiri Mohammadabad social trust (2015) and Scheier and Carver optimism (1985). To analyze data were used from Pearson correlation and multiple regression with enter method tests in SPSS software. Findings from Pearson correlation test showed that social trust and optimism had a significant positive relationship with social development and findings from multiple regression with enter method test showed that social trust and optimism were able to significantly predict social development and were able to predict 32.4% of its changes in the faculty members of Islamic Azad Universities of Mazandaran province that the share of social trust was more than optimism (p < 0.01). According to the results of this study, planning to promote the social development of faculty members is essential by increasing social trust and optimism. Therefore, by holding in-service courses and necessary training can by improving social trust and optimism in faculty members improve the level of their social development. Manuscript profile -
Open Access Article
275 - Effectiveness of spirituality therapy training based on positivity on happiness and optimism in adolescents
saman kamari رقیه زارعی محمدباقر ریحانی لیلا شیرجنگ احمدعلی امامیIntroduction: many researches have been shown the effectiveness of spirituality therapy in treatment of mental illness such as depression and anxiety and recently from spirituality therapy approach also used for to improvement of the level of individual’s happines MoreIntroduction: many researches have been shown the effectiveness of spirituality therapy in treatment of mental illness such as depression and anxiety and recently from spirituality therapy approach also used for to improvement of the level of individual’s happiness and optimism. Therefore the purpose of this study was to investigate the effectiveness of spirituality therapy training based on positivity on happiness and optimism in adolescents. Methods: The Methods of present study was a semi-experimental research and a pretest- posttest design with control group. The statistical population were included all high school students in the first grade (year) in Shiraz city that 60 of them were selected through convenience sampling and then based on random assignment of subjects divided into experimental and control groups (each group include 30 subject). The subjects responded to Oxford happiness questionnaire and Life Orientation Test (LOT). the data of research was analyzed using univariate analysis of covariance (ANCOVA) method. Finding: the univariate analysis of covariance showed that spirituality therapy training had significant effect on increasing happiness in experimental group (P<0/044), also Spirituality therapy training to increase optimism experimental group with the significance level (P<0/017). Conclusion: generally finding showed that spirituality therapy not only in treatment of the types of mental illness was effectiveness but also it can be used for increase the level of happiness and optimism in individuals. Manuscript profile -
Open Access Article
276 - Comparative Comparison of Ideology Layers of the Poems by Farrokhi Yazdi and Aref Ghazvini
fazlollah rezaii erdaniFarrokhi Yazdi and Aref Ghazvini are famous figures in the constitutional era, whose lives have been linked with events of his age. They fight with their weapons of poetry against oppression and oppression of life and oppression. From the very beginning, they express th MoreFarrokhi Yazdi and Aref Ghazvini are famous figures in the constitutional era, whose lives have been linked with events of his age. They fight with their weapons of poetry against oppression and oppression of life and oppression. From the very beginning, they express their support and support for the constitutional movement, and they express their lyrics. After constitutional movement, they continue to struggle with the elements of internal tyranny and foreign colonialism, and they endure a lot of hardship and suffering, but they do not stop fighting. Finally, Farrokhi is being killed in prison by the hands of our ancestors, and the mystic lives in exile, loneliness and isolation. The main task of the poetry of Farkhi and Arif is the awakening of a mass of people. Their ideology is based on events and time requirements. Most of their poems are related to social and political issues. Comparing their ideological ideas shows that their thoughts are close together. In this research, we try to show the ideological thoughts of these two prominent poets of the Constitutional Revolution in political, social and religious matters with poetical evidence Manuscript profile -
Open Access Article
277 - Counsel in The National Epics of Iran
Hadi YousefiIn this paper, counsel and consultation among the negative characters, or antagonists, in the national epic of Iran, are reviewed in analytic-descriptive approach. Antagonists and, in some occasions, generals consult with officials when important issues determini MoreIn this paper, counsel and consultation among the negative characters, or antagonists, in the national epic of Iran, are reviewed in analytic-descriptive approach. Antagonists and, in some occasions, generals consult with officials when important issues determining the future of wars and the destiny of kings’ realms, are concerned. Based on mentioned above, the function of antagonist’s counselors is analyzed and divided into two categories: first , offering helpful resolutions when antagonists encounter and fight against protagonists and their army ; second ,sleep interpretation and prediction. In accordance with carried out studies, antagonists’ counselors include ministers,zorasterian clergymen ,astrologers, fortunetellers, generals and antagonists’ close relatives , alliances and in some cases the armies that each group assist the antagonists with their opinions to make decisions especially about their territory and the army. Manuscript profile -
Open Access Article
278 - Sayyid Qutb and Persian poetry (Reflecting his appreciations regarding Hafez and Khayyam's poetry)
Marziyeh nadafi Seyed ahmad hoseyni kazeroni Shams alhajeyeh ardalani Davood yahyaeiSayyid Qutb is one of the prominent figures of the twentieth century. He is considered as a religious and political intellectual, and his views regarding literature and poetry is subject to consideration. Studying Hafez and Khayyam poetry, he has critically studied thei MoreSayyid Qutb is one of the prominent figures of the twentieth century. He is considered as a religious and political intellectual, and his views regarding literature and poetry is subject to consideration. Studying Hafez and Khayyam poetry, he has critically studied their poem and believes that these two Persian literary figures can be classified among mystical poets. Hafez, in general, is poet with great wit and humor mixed whit romantic ideas and occult knowledge, and Khayyam, according to him, is a grieved Sufi and poet searching for the lost truth failing to find a ray of light in darkness. Sayyid Qutb's appraisals on the one hand indicates the degree of familiarity with the Iran's literature and culture and, on the other hand, reveals his detailed studies concerning the great poets of Iran. This paper aims at considering his critical appraisals and appreciation regarding two Iranian poets. Manuscript profile -
Open Access Article
279 - Predictive model of administrative system transformation in the field of human resources
Reza Farahmand Sanjar Salajegheh Masoud Pourkiani Saeed SayadiThe aim of this study was to design a model for predicting the evolution of the administrative system in the field of human resources. The existing research is applied and developmental in terms of purpose and a mixed exploratory research in terms of method. The statist MoreThe aim of this study was to design a model for predicting the evolution of the administrative system in the field of human resources. The existing research is applied and developmental in terms of purpose and a mixed exploratory research in terms of method. The statistical population of the study included all employees of the executive bodies of Kerman in the number of 23,270 people who were selected as a sample using stratified random sampling method of 450 people. To collect data, two researcher-made questionnaires were used to prevent the implementation of administrative system transformation in the field of human resources and administrative system transformation. The results showed that the conceptual model of the research has an acceptable fit and the factors hindering the evolution of the administrative system in the field of human resources are: Inadequacy, inadequate education, lack of welfare, inadequate retirement benefits, inadequate evaluation, high degree of politicization, bureaucratic domination, institutional, technical and administrative incompetence, Lack of attention to the simultaneous implementation of public interests and administrative rights, weakness of information and communication technologies, lack of effective causal conditions, cultural, political, managerial, judicial, value and structural factors, ambiguity of goals and lack of dominance of continuous improvement thinking, These factors explain 0.35 of the variance of the administrative transformation system in the field of human resources. Manuscript profile -
Open Access Article
280 - Prediction of Residual Gas Consumption using Temperature and Population of ConsumersUse case : Residual Consumers of Karaj
Masoud Akbari Mahdi Asghari Aliakbar Imami Satlou Parham Davari Shahnaz Salamat Thani Nahid Taherian Mansour GholinejdaNatural gas has a vital role as energy supplier in Iranian residual regions. According to reports of manager of dispatching department of National Iranian Gas Company, residual consumers had a share of 70 percentage of all manufactured natural gas, on cold days of 2021. MoreNatural gas has a vital role as energy supplier in Iranian residual regions. According to reports of manager of dispatching department of National Iranian Gas Company, residual consumers had a share of 70 percentage of all manufactured natural gas, on cold days of 2021. Also about 88 percentage of the country's electricity is supplied by fossil fuels, based on the report of Water and Electricity Industry. All of these statistics warn us about the importance of residential gas management. In this article, a nonlinear regression model was produced based on temperature and population of residential consumers in different periods of year. Also consumptions of residential consumers of Karaj city used to evaluate performance of the model. Results show that there is a meaningful correlation between selected features and consumed amount of natural gas that can help us to predict consumption more accurate in future. Manuscript profile -
Open Access Article
281 - Effectiveness of Peace Education on increase of Hope and Optimism in middle school students in District 3 of Tehran
Amirmasoud Rostami Hasan Ahadi Khadijeh Abolmaali Fariborz DortajPurpose: The aim of this study was to determine the effectiveness of peace education on increasing optimism and hope in junior high school male students.Methodology: The present study method was performed. is using quasi-experimental method with pretest-posttest design MorePurpose: The aim of this study was to determine the effectiveness of peace education on increasing optimism and hope in junior high school male students.Methodology: The present study method was performed. is using quasi-experimental method with pretest-posttest design by considering one experimental group and one control group with two-month follow-up. The statistical population of the study included male first-grade high school students in District 3 of Tehran. A total of 60 samples were randomly selected and according to the inclusion and exclusion criteria, they were voluntarily assigned into two groups of experimental and control (30 in each group). The data collection tools included Luthans (2007) Psychological Capital Scale. The peace education intervention program was implemented in eight 120-minute successive sessions based on the developed protocol in person After school closure. To analyze the data, the analysis of variance with repeated measures (mixed design) was used. Results : Results revealed that implementation of peace education in comparison with the control group significantly affected the components of hope and optimism in students and the results of multivariate analysis showed that the effectiveness of peace education and the components of hope and optimism at the 0.01 level .Conclusion: Thus, it can be concluded that providing peace education to students leads to sustainable increase in their hope and optimism. Manuscript profile -
Open Access Article
282 - Exploitative leadership and employees' creativity: An analysis of the mediating role of organizational cynicism
Mohsen Aref Nezhad Fariborz Fathi Chegeni Ahmad Ghobadi Alvar Mohammad Hatami NeghadContext: In today's era, it has become clear to everyone that the existence of creative and motivated human resources is one of the reasons for the economic leadership of organizations and their not falling behind in the field of competition. Meanwhile, various factors MoreContext: In today's era, it has become clear to everyone that the existence of creative and motivated human resources is one of the reasons for the economic leadership of organizations and their not falling behind in the field of competition. Meanwhile, various factors affect the creativity of employees, which include exploitative leadership and organizational cynicism.Objective: The purpose of this research was to examine the relationship between exploitative leadership and employees' creativity with the mediating role of organizational cynicism in Lorestan University.Research method: The present descriptive-exploratory research is applied in terms of purpose and is based on the deductive research and positivism paradigm in term of philosophy. The statistical population of the study was 440 employees of Lorestan University. Based on Morgan's table, a sample of 205 people was selected by stratified random sampling. In order to measure the variables of the research, the (Schmid et al’s, 2019) exploative leadership Questionnaire, (Wang et al’s, 2013), creativity Questionnaire and the (Dean et al’s, 1998) organizational cynicism Questionnaire were used and Their reliability was confirmed by Cronbach's alpha. For data analysis, structural equations modeling and PLS software have been used.Findings: Findings show that exploative leadership has a negative and significant relationship with employees' creativity and a positive and significant relationship with organizational cynicism, organizational cynicism has a negative and significant relationship with employees' creativity, also exploative leadership has a significant negative relationship with employees' creativity through organizational cynicism.Conclusion: Exploitative leaders who, with all their selfishness, are highly focused on achieving their personal goals and do not spare any effort in this direction, have caused dissatisfaction and a feeling of organizational cynicism in employees, which causes negative thoughts towards The organization and the feeling of frustration and discouragement among the employees will increase, as a result of which their creativity will decrease. Manuscript profile -
Open Access Article
283 - Comparison of the effectiveness of optimism training, emotion regulation and mindfulness training in reducing academic burnout in students with test anxiety
Amirreza Rasam Ozra Ghaffari Abbas Abolghasemi Mansour BeyramiTest anxiety is one of the most common problems among students that causes behavioral problems in addition to academic problems. Exam anxiety is associated with a variety of factors, and there are various ways to do it. One of the factors associated with exam anxiety is MoreTest anxiety is one of the most common problems among students that causes behavioral problems in addition to academic problems. Exam anxiety is associated with a variety of factors, and there are various ways to do it. One of the factors associated with exam anxiety is students' academic apprehension. The purpose of the present study was to compare the effectiveness of different educational programs (optimism, emotion regulation and mindfulness) in reducing academic anxiety in students with test anxiety. In this regard, four groups of students with test anxiety were randomly selected and three groups were trained as program (optimism, emotion regulation and mindfulness) for eight sessions and one group as control group. The results of pre-test and post-test of groups on students' academic achievement were compared and analyzed using multivariate analysis of covariance (ssps). In the present study, the results showed the effectiveness of all three methods of training in reducing academic burnout, but mindfulness training was the most effective method with the highest difference, followed by optimism and emotion regulation. Manuscript profile -
Open Access Article
284 - The Role of optimism in the Relationship between Social Support and Treatment Adherence of Hepatitis Patients in Zanjan
Mina Kamran Haghighi Masoud Hejazi Afsaneh SobhiPurpose: Hepatitis is a major health problem in the world and is one of the ten leading causes of death in humans. This disease is an important cause of cancer and liver disorders and causes disabilities in people. The aim of this study was to determine the role of opti MorePurpose: Hepatitis is a major health problem in the world and is one of the ten leading causes of death in humans. This disease is an important cause of cancer and liver disorders and causes disabilities in people. The aim of this study was to determine the role of optimism in the relationship between social support and treatment adherence of hepatitis patients in Zanjan. Methodology: The method of this research was correlational. The statistical population of the study included all patients with hepatitis referred to the Comprehensive Health Center No. 5 in Zanjan in the first half of 2019 were 999 people, who 210 patients was selected by accessible randoming in the study. To collect the required data, McLean (1993) Ambiguity Tolerance Questionnaire, Sherborne & Stewart (1991) Social Support Questionnaire and Moriski et al. (2008) treatment adherence questionnaire were used to collect the required data. Also, Pearson statistical tests and multiple regression in Spss software version 25 were used to analyze the data. Significance level was considered 0.05 for all tests. Findings: The results showed between social support with treatment adherence (P<0.001, r= 0.360), between social support with optimism (P<0.001, r= 0.329) and also between optimism. There was a direct and significant correlation with treatment (P <0.001, r= 0.349). The results also showed that the effect of total social support on optimism was significant (P<0.001, β= 0.442). The partial mediating role of optimism in the relationship between social support and treatment adherence was significant (P<0.05). Conclusion: In general, the results of this study showed that social support with partial mediation of optimism was significantly associated with treatment adherence of hepatitis patients. Manuscript profile -
Open Access Article
285 - Investigation and Prediction of Spatial and Temporal Land Use Changes in New Hashtgerd City by Integrating Remote Sensing Data and Cellular Automata Markov model
Sara SoukhtezariLand use changes due to the physical expansion of the city in most cities in Iran are so rapid, that urban planners and managers are facing a dynamic and complex development as they integrate the planning process in these areas. The purpose of this study is to investiga MoreLand use changes due to the physical expansion of the city in most cities in Iran are so rapid, that urban planners and managers are facing a dynamic and complex development as they integrate the planning process in these areas. The purpose of this study is to investigate land use changes and physical development of Hashtgerd city during the past 19 years and to predict land use change trends for the future. In this study, Landsat multi-time images were used. Using the support vector classification machine algorithm and the algorithm for Cross-Tab change, land use change trends over the past 19 years was evaluated. Also, using the Cellular Automata Markov prediction model, the process of land use change and physical expansion of the city is predicted for the future. The results of this study indicate the unnecessary expansion of the city over the past 19 years. So that the built-up with 736.56% growth have caused excessive destruction of agricultural and bare lands on the outskirts of the city. Investigations show that with increasing distance from land use changes have significantly reduced the amount of land use. Investigation of changes in land uses showed that 564/166 hectares of waste land has become residential land use. Predicting land use changes for 2028 and 2038 showed that residential land use will continue to increase. This highlights the need for special attention of urban planners and managers to the issue of urban development and its consequences in the region. Finally, the evaluation of the accuracy of the automated cell model showed that the percentage of classes area difference was less than 8%. Manuscript profile -
Open Access Article
286 - Prediction of Urban Construction Changes Using Satellite Images Based on CA-MARKOV Models (case study: Sari)
Sahab Bidgoli Kashani Mehran Fadavi Valiollah AzizifarAlong with the ever-increasing urban population, the amount of construction in the city space has been developed. The development of construction in the horizontal space and regardless of the existing restrictions has led to environmental, economic and legal problems fo MoreAlong with the ever-increasing urban population, the amount of construction in the city space has been developed. The development of construction in the horizontal space and regardless of the existing restrictions has led to environmental, economic and legal problems for the citizens. Achieving the amount, intensity and direction of construction development from the past to the present and predicting the construction situation in the future is the first step towards the scientific and practical management of the physical development of urban construction, planning and providing suitable solutions in order to create a balance between allocation Spatial-spatial construction and all kinds of legal, economic and environmental considerations. Data and information extracted from satellite images, while showing the historical changes of urban construction, are used as the main, necessary and necessary input data for models to predict its future state. In this research, satellite images of TM, ETM+ and OLI sensors of Landsat satellite were used in the time periods of 1997-2007 and 2007-2017 related to the city of Sari. After performing geometrical corrections, city area maps were prepared. Then, by using the effective parameters in urban construction changes, using the Cellular Automata(CA) Markov Model, the accuracy of the simulations was checked. Finally, for validation, the simulated maps and the ground reality map were matched with each other. The simulation of the construction development process in 2027 using the CA-Markov model showed that if the existing management regulations continue, this area will decrease from 4617.90 hectares in 2017 to 4357.44 hectares in 2027. But the examination of change maps and stability maps showed that new areas will be under construction between 2017 and 2027, which were mainly used for agriculture and barren land. Manuscript profile -
Open Access Article
287 - اثر عوامل مالی رفتاری بر ارزش معاملات در شرایط مختلف بازار سهام
علی رضاییان محمد اسماعیل فدایی نژاد ابراهیم جوشن -
Open Access Article
288 - اثرپیش بینی سود بر رابطه ارزش و ریسک پذیری شرکت در شرکت های پذیرفته شده در بورس اوراق بهادار تهران
اکرم تفتیان فائزه شجاعی فر -
Open Access Article
289 - نقش پیشبینی های تحلیلگران جریان نقد در ناهنجاری اقلام تعهدی
وحید بخردی نسب فاطمه ژولانژاد -
Open Access Article
290 - بررسی تاثیر تغییرات سود حسابداری شرکتها بر پیش بینی تولید ناخالص داخلی در شرکتهای پذیرفته شده در بورس اوراق بهادار تهران
علی محمدی محمد کابلی -
Open Access Article
291 - ارزیابی عملکردشرکت بابرّرسی تأثیرتیزبینی بازارومشارکت شبکه تأمین،برقابلیت مقاومت دربرابررخدادهای فاجعه بار
علیرضا فضل زاده محمد صبوری فرد محمدرضا قربانیان جعفر امینی -
Open Access Article
292 - A Non-deterministic CNN-LSTM Hybrid Model for Bitcoin Cryptocurrency Price Prediction
علی علی جماعت سید محسن میرحسینیAbstractIn today's society, investment diversity has become very important. People reduceinvestment risk by diversifying their portfolios. Bitcoin has gained muchpopularity as one of the digital capitals and has been included in the investmentportfolio of individuals an MoreAbstractIn today's society, investment diversity has become very important. People reduceinvestment risk by diversifying their portfolios. Bitcoin has gained muchpopularity as one of the digital capitals and has been included in the investmentportfolio of individuals and institutions. Bitcoin price prediction is essential fordetermining price trends and transactions. For this purpose, various traditionalmethods as well as methods based on machine learning have been presented, eachof which has its own advantages and disadvantages. Recently, the use of hybridmodels has received attention. Combined methods have good efficiency and usethe advantages of combined techniques. This paper presents a hybrid methodbased on a deep convolutional neural network and recurrent neural network withprobabilistic dropout. Eliminating possible randomness leads to the regularizationof learning, avoids overfitting, and reduces model error. The results of theexperiments show that the proposed method has a higher accuracy than thecompared methods in predicting the price of Bitcoin. Manuscript profile -
Open Access Article
293 - Preliminary Report on Archaeological Survey of Komijan, Markazi Province
Gholam Shirzadeh Esmail Sharahi Ghafour KakaThese days the role of middle- point regions is one of the important issues for archaeological researchers due to their importance in political, economic, social and cultural interactions. Archaeological surveys have important role for knowing of political and cultural MoreThese days the role of middle- point regions is one of the important issues for archaeological researchers due to their importance in political, economic, social and cultural interactions. Archaeological surveys have important role for knowing of political and cultural changings in various regions. One of the goals of the Komijan Town survey and studying is reaching to the role of the middle- point regions during the different periods of human life in the region. Komijan Town is located between the center of Iranian plateau and Zagros. This town had had role in the cultural communications. The region has been consisted an immense plain with ranges around it. Mentioned plain is bounded on the west by Famenin Plain in Hamedan and on the south by Shaara greens valley. It has been a place of settlement for human groups in different periods in comparison with regions of piedmont and has had the main role in regional communications as well. Qara Chay River is the most important river of the region that is came at the part of the plain. Komijan Town archaeological survey carried out in 2009 in 1625 square kilometers space. At the end of the survey has identified 90 footprints relating to prehistoric era until contemporary centuries: sites, petrology and historical buildings. Manuscript profile -
Open Access Article
294 - فصلنامه علوم رفتاری/173 بررسی تأثیر بدبینی سازمانی بر تغییرات سازمانی در بین کارکنان بانک سپه سرپرستی جنوب تهران
جواد محرابی مرتضی استیری -
Open Access Article
295 - Molecular docking and ADMET prediction of active compounds in Tualang honey against Sex hormone-binding globulin (SHBG) for the treatment of male infertility
Hamed Shahriarpour Mostafa Ghaderi-ZefreheiIntroduction: Sex hormone-binding globulin (SHBG) is a protein that is synthesized by liver cells and binds to sex hormones to regulate their levels and bioavailability. Its binding to testosterone reduces bioavailable testosterone and causes diseases of the male reprod MoreIntroduction: Sex hormone-binding globulin (SHBG) is a protein that is synthesized by liver cells and binds to sex hormones to regulate their levels and bioavailability. Its binding to testosterone reduces bioavailable testosterone and causes diseases of the male reproductive tract such as infertility, erectile dysfunction and prostate cancer. Objective: In this in Silico study, the potential of several compounds present in Tulang honey against SHBG protein for the treatment of infertility has been investigated. Materials and methods: The six compounds in Tualang honey, Catechin, Ethyl oleate, Fisetin, Hesperetin, Kaempferol and Luteolin were obtained from previous studies and the PubChem pharmaceutical database. The binding energy and type of protein-ligand interactions were investigated by molecular docking of these compounds to SHBG protein. AutoDock Vina version 1.1.2 software was used to perform molecular docking and Discovery Studio v21.1.0.289 software was used to analyze molecular docking results. Then SwissADME and admetSAR 2.0 web servers were used to evaluate the pharmacokinetic properties of these compounds through ADMET predictions. Results: The binding energy obtained from molecular docking showed that Luteolin with a score of -10 kcal/mol binds to SHBG protein, and has more hydrogen-hydrophobic interactions than other studied compounds as well as compounds that have been worked on in recent papers. Catechin and Fisetin also showed an acceptable result. The study of ADMET and bioavailability radar showed that although these compounds have physicochemical properties for use as drugs, they have the potential to inhibit some cytochromes and toxicity for certain organs and DNA or other genetic material in the body that should be considered in the use of these compounds as drugs. Discussion and conclusion: Using this in silico study, several suitable molecules of natural origin against the SHBG protein were identified, which showed potential for the treatment of male infertility. Manuscript profile -
Open Access Article
296 - تحلیل تغییرات کاربریهای اراضی نواحی حاشیه زاینده رود با مدلسازی در سامانه اطلاعات جغرافیایی (بازه چم خلیفه تا سامان شهرکرد)
علی اکبر جمالی سید علی المدرسی احسان ایزدی -
Open Access Article
297 - تحلیلی بر تأثیر فرهنگ در ساخت شهرهای ایرانی اسلامی
سعید امانپور جعفر سعیدی -
Open Access Article
298 - کاربست جهان بینی اسلامی در شهرهای ایرانی- اسلامی با تأکید بر توسعه پایدار محله ای
محمد کاظم شمس پویا ابوالفضل مشکینی مجتبی برغمدی -
Open Access Article
299 - مقایسه تطبیقی شاخص های کمی و کیفی مسکن مناطق 22گانه شهر تهران در سال 1395 و پیش بینی ابعاد اجتماعی مسکن در سال 1405
احمد پوراحمد شهلا عباسی -
Open Access Article
300 - Predicting the academic performance based on academic vitality, achievement motivation and academic optimism in students
Samineh Bahadori Jahromi Rohollah Cheraghpour Soheila PayanThis study aimed to predicting the academic performance based on academic vitality, achievement motivation and academic optimism in students. Present research was descriptive-analytical from type of correlation. The statistical research population was high school studen MoreThis study aimed to predicting the academic performance based on academic vitality, achievement motivation and academic optimism in students. Present research was descriptive-analytical from type of correlation. The statistical research population was high school students of BandarAbbas in 2018-19 academic years. Research sample were 600 students (300 girl and 300 boy) who were selected by multistage cluster sampling method. To collect data used from the questionnaires of academic performance (Salehi, 2013), academic vitality (DehghaniZadeh & HoseinChari, 2012), achievement motivation (Hermans, 1970) and academic optimism (Beard & et al, 2010). Data were analyzed in SPSS-19 software by Pearson correlation coefficient and multiple regression with enter model methods. The results of analysis showed that academic vitality, achievement motivation and academic optimism has a positive and significant relationship with academic performance of students. Also, the variables of academic vitality, achievement motivation and academic optimism significantly could explain 23 percent of variance of academic performance of students (p < 0/01). Therefore, in order to improve academic performance of students it is recommended to increase their academic vitality, achievement motivation and academic optimism through workshops. Manuscript profile -
Open Access Article
301 - Investigating components of psychological capital in higher education to present a model
behrang esmaeili kiuomaezh niyazazari mohammad salehi taraneh anayatiThis days scientists think that mere material, human and social capital are sufficient for success in organizations but staffs’ positive psychological components are more important. Regarding the importance of psychological comp MoreThis days scientists think that mere material, human and social capital are sufficient for success in organizations but staffs’ positive psychological components are more important. Regarding the importance of psychological components in organization and management, special kind of capital termed Psychological capital is becoming important. The aim of this research is to verify and recognize the positive psychological components of the capital. Research population is the faculty of branches of Islamic Azad University located in Mazandaran. A sample was selected using stratified sampling. The factor analysis results show that 100 components are recognizable. Correlation Matrix is used to construct the model Manuscript profile -
Open Access Article
302 - The relationship between psychological capital and job satisfaction East Mazandaran Province Imam Khomeini Relief Committee
A.GH Barimani یاسمن Madanlo حبیب اله Yosefi -
Open Access Article
303 - c
abolghasem barimani yasaman madanlou habiballah yousefe -
Open Access Article
304 - Relationship between accounting information quality criteria in response to managers' motivational components
Abdullah Hosseinzade Mahmoud mousavi shiri zohreh hajiha Hashem NikoomaramPast studies have used various criteria to measure the quality of accounting information, each of which indicates a specific dimension of quality. The purpose of this study is to provide a framework for evaluating and comparing the criteria of accounting information qua MorePast studies have used various criteria to measure the quality of accounting information, each of which indicates a specific dimension of quality. The purpose of this study is to provide a framework for evaluating and comparing the criteria of accounting information quality including persistence, predictability and accrual quality in response to the motivational components of rewards, debt, policy and tax. This research is of applied type and has been done with correlation approach. The statistical sample of the research includes 163 companies listed on the Tehran Stock Exchange in the period 2009 to 2017. The collected data were analyzed by combined data and least squares regression. The research findings show that reward motivation has a significant relationship with all quality criteria of accounting information. In a way that with increasing motivation, rewards, persistence and accrual quality increase and predictability decreases. Also, the criteria of accounting information quality in response to management motivations have significant convergence, divergence and lack of relationship. Manuscript profile -
Open Access Article
305 - Forecasting the exchange rate using futures studies methods and examining the effect of currency fluctuations on the performance of companies: A case study of Iran Tobacco Company
Alireza Fathinia Ali BadizadehExchange rates always have a high priority and attractiveness in society, especially among companies. Different methods are used to predict the exchange rate, among which structural methods as methods of fundamental analysis, a little precision in advance. They have an MoreExchange rates always have a high priority and attractiveness in society, especially among companies. Different methods are used to predict the exchange rate, among which structural methods as methods of fundamental analysis, a little precision in advance. They have an accurate forecast of the exchange rate, but they are very useful as a long-term perspective and illuminate the movement of the exchange rate. Technical compensation can be used to compensate for the shortcomings of these methods. Using futures research techniques, in addition to covering the study gap of futures research techniques in forecasting exchange rates, errors due to quantitative methods have been minimized so that companies are prepared for the occurrence of various situations. In the final part of the article, the effect of currency fluctuations on the performance indicators of the tobacco company during the last three years is examined. The results of the study indicate that currency fluctuations have the first and greatest impact on the implementation of development projects and also sudden economic shocks are not immediately reflected in the performance of companies and due to the presence of shock absorbers such as inventory in Warehousing, borrowing purchases and long-term debt creation, over time, gradually affect and weaken the company's performance. Manuscript profile -
Open Access Article
306 - Providing a Model for Predicting the Success of Investment Projects in Free and Special Economic Zones, Using the Multi-Layer Neural Network Technique
morteza shokrzadeh kamaleddin rahmani farzin modares khiyabani majid bagherzadehTo analyze the data of this research, descriptive statistics and inferential statistics were used and experts selection software, MATLAB, SPSS and PLS software were employed Using theoretical foundations and libraries, six effective factors and variables predicting the MoreTo analyze the data of this research, descriptive statistics and inferential statistics were used and experts selection software, MATLAB, SPSS and PLS software were employed Using theoretical foundations and libraries, six effective factors and variables predicting the success or failure of Investment projects in the free and special economic zones of the country were identified.After describing the variables and testing the normality,using the PLS software, a confirmatory factor analysis of the variables was carried out, in which all of the factors had a good confirmatory factor analysis and all the questions were approved Then, using linear regression and ANOVA, the effect of each of the factors on the success or failure of investment projects was investigated, and the results of this test showed confirmation of the impact of each of the factors, and then the results of the hierarchical analysis indicated this was the first rank of product and service, followed by the second-rank ,that is geographical considerations, and the characteristics of the investor's psychology, the third rank, the product market characteristics, the fourth rank, the investor's ability to rank fifth, and financial considerations ,also, earned the last rank.Considering this prioritization, the neural network used in this research contained data from 6variables as an input variable, with two intermediate layers with 30 nodes in the first layer, and three nodes in the second layer, which had one outlet.The results indicated that the neural network model had the power to predict the success of the investment projects. Manuscript profile -
Open Access Article
307 - Presenting a model for predicting tax evasion guilds based on Data mining techniques
Mohammad Ghasemi Sadegh Abedi Ali MohtashamiIn this research, considering the importance of the topic and deficiency in previous researches, amodel for predicting tax evasion of guilds based on data mining technique is presented. Theanalyzed data includes the review of 5600 tax files of all guilds holding tax cod MoreIn this research, considering the importance of the topic and deficiency in previous researches, amodel for predicting tax evasion of guilds based on data mining technique is presented. Theanalyzed data includes the review of 5600 tax files of all guilds holding tax codes in Qazvinprovince during the years 2014-2019. The tax file related to guilds is in five tax groups includethe guild group of owners of notary public offices, the guild group of real estate agencies, theguild group of catering halls, restaurants and related businesses, the guild group ofcommunication services, and the guild group of exhibitions and auto accessories stores andrelated businesses. For modeling, the classification model including the decision tree algorithmwas used. The results indicate that the coverage criterion is 68%, the Kappa criterion is 0.612,which indicates the good performance of the modeler. Also, using the Cross Validationtechnique, the validity of the prediction model was tested in order to more reliably estimate thepercentage of modeling performance. The accuracy criterion equal to 67.79% shows theappropriate reliability for the prediction model. The results of this research can be utilized informulating operational strategies based on data mining to predict the tax evasion of guilds in theprovinces. Manuscript profile -
Open Access Article
308 - Optimization ELM neural network in prediction problem: case study forecasting demand steel in Iran
Jalal Rezaeenour Mansoureh Yari eili Esmaiel roozbahani Mohammad hossein RoozbahaniPrediction of supply and demand, is a crucial issue for supply chain partners. With the accurate forecasted supply and patterns that indicate the sizes and directions of future production flow, the government and suppliers can have a well-organized strategy and provide MorePrediction of supply and demand, is a crucial issue for supply chain partners. With the accurate forecasted supply and patterns that indicate the sizes and directions of future production flow, the government and suppliers can have a well-organized strategy and provide a better infrastructure for improving industrial sector.With the aim of developing accurate forecasting tool in steel industry, this study present a new optimized neural network, by combination of Extreme Learning Machine and genetic algorithm. We employed our model on a dataset for steel supply - demand in Iran from jul-2009 to jan2013 to estimating the performance. The results show that prediction accuracy and performance relatively better than other classical approaches, according to RMSE and MAPE evaluations. In our model. Based on statistical tests, our new model is better than other model in accuracy, so can be used in as a suitable forecasting tool in steel supply forecasting problems. Manuscript profile -
Open Access Article
309 - Dynamic Algorithm Design for Data Mining and Accurate Prediction of Customer Response
Mehdi Zakipour Sina Nematizadeh MohamdAli AfsharkezemiThe problem of identifying and anticipating potential customers to be addressed at direct marketing programs has been considered as one of the popular and most important marketers' issue. Marketers who use these approaches are threatened by the severe reaction of those MoreThe problem of identifying and anticipating potential customers to be addressed at direct marketing programs has been considered as one of the popular and most important marketers' issue. Marketers who use these approaches are threatened by the severe reaction of those consumers who consider the direct marketing as an attack to their private lives, so it may even be possible to boycott companies that use these methods. Neural networks are known as a powerful tool for prediction, but as previously mentioned, as with other prediction algorithms, they tend to deviate toward imbalanced data. In this research, in order to enhance the ability to identify and predict potential customers by multilayer perceptron networks, using Random under-over sampling methods, which has been used frequently in other articles, we attempted cluster customers and create different combinations of them, and then from the observed results, we finally introduced an innovative and highly efficient method for identifying and rating potential customers. The results indicate that, in addition to the undeniable power of multilayer neural networks in the field of identification and prediction, imbalanced data has greatly damaged the results. In this regard, creating an optimal combination of customer data and implementing the innovative algorithm of the present study significantly improves the results and the performance of artificial neural networks has yielded a reliable consequences. Manuscript profile -
Open Access Article
310 - The Impact of Employability on Career Success of Employees at Qazvin Product Distribution Company
Seyyed Mohammad Zahedi Soheila ZakizadehPresent research addresses the impact of employability on career success of employees of Qazvin Province National Oil Product Distribution Company. Statistical population of present research consisted of 203 employees of Qazvin Province National Oil Product Distribution MorePresent research addresses the impact of employability on career success of employees of Qazvin Province National Oil Product Distribution Company. Statistical population of present research consisted of 203 employees of Qazvin Province National Oil Product Distribution Company. 190 subjects were selected, using simple random sampling. The first research instrument was van der Heijden and van der Heijden’s Employability scale with five dimensions of occupational expertise, anticipation and optimization, personal flexibility, corporate sense and balance. The second instrument utilized in this study was Gautier and Linwood's Career Success Scale with five dimensions of job success, interpersonal success, financial success, hierarchical success and life satisfaction. Reliability of instruments was verified using Cranach Alpha which were 0.925 and 0.903 respectively for first and second one. Data analysis was performed using simple linear regression. Results showed that employability dimensions had significant effect on career success. Manuscript profile -
Open Access Article
311 - Forecasting Daily Volatility and Value at Risk with High Frequency Data
Amir Mohammad Zadeh Sahar Masoud ZadeganOne of the key aspects in the financial markets and its development is fluctuation. Fluctuation plays a key role in option pricing, portfolio management and the market sentiment. In general, financial institutions are faced with four various kinds of risk, which are cre MoreOne of the key aspects in the financial markets and its development is fluctuation. Fluctuation plays a key role in option pricing, portfolio management and the market sentiment. In general, financial institutions are faced with four various kinds of risk, which are credit risk, liquidity risk, operational risk, and market risk. The most appropriate method to measure the market risk is by using the VaR (value at risk). Value at Risk is statistical technique used to measure and quantify the level of financial risk within the investment portfolio over a specific time frame. It is always expressed by the monetary amount that is at risk as well as the probability of loss. This research is to predict the VaR for a one-day period in six different industries in which three companies are monitored in each industry. The time periods of the study are 30-minute intervals between 91/11/1 to 92/4/1, in which the GARCH model is used for predicting the variance. The research then checks to see whether the data fits the normal or t-distributions models. Thus, six models are used for six different industries. All six chosen models are deemed proper to predict the coefficients, how fit the coefficients are, and Watson statistic camera. The estimation of the variance and the Var for all models is done at a %95 confidence interval. The research concludes that the companies involved in the basic metals group are more prone to risk and have higher VaR in comparison to other industries. Manuscript profile -
Open Access Article
312 - Using different learning algorithms in the stock price prediction by using neural networks
Reza Kiyani Mavi Kamran Sayadi NikStock price prediction is a very important financial topic, and is considered a challenging task and worthy of the considerableattention received from both researchers and practitioners. Stock price series have properties of high volatility, complexity,dynamics and turb MoreStock price prediction is a very important financial topic, and is considered a challenging task and worthy of the considerableattention received from both researchers and practitioners. Stock price series have properties of high volatility, complexity,dynamics and turbulence, thus the implicit relationship between the stock price and predictors is quite dynamic. Hence, it isdifficult to tackle the stock price prediction problems effectively by using only single soft computing technique.In this research, in the first step, the possibility of predicting stock price of National Iranian Copper Industries Company wasstudied. Then, for predicting of stock price after one day neural ¬network of MLP by learning algorithm of Levenberg-Marquardt were used. Then optimize structure of neural network was trained with the standard BP algorithm, the learningrate is 3/0 has the best performance. And for this learning rate, sensitive of standard BP algorithm was calculated to minimizelocal. At the end, standard BP algorithm with momentum is used. The results showed that predicting by standards BPalgorithm with momentum is better than the standard BP algorithm. Manuscript profile -
Open Access Article
313 - Positive Psychological Capacities and Organizational Commitment
Sayed Mohammad Kamani Maryam Shaer Khadijeh NamdariPaying attention to the issue of manpower is considered as one of the most critical challenges of organizations in today’s competitive age, as one of the most important indicators of Progress and Excellence are committed and loyal workforce. This research was done MorePaying attention to the issue of manpower is considered as one of the most critical challenges of organizations in today’s competitive age, as one of the most important indicators of Progress and Excellence are committed and loyal workforce. This research was done with the purpose of Surveying the relationship between Kazeroon education employees' positive psychological capacities including hope, optimism and resilience; and their organizational commitment (affective, normative and continuance). The population of the present research consists of 855 Kazeroon education employees including staff, managers, assistants and teachers who work in high schools and guidance schools of whom 265 employees were selected as sample using Classification method and Morgan’s table. Research method is descriptive and the data collection tool is questionnaire. The collected data were analyzed by means of a software application. Descriptive statistics including frequency tables, graphs, mean, and standard deviation and inferential statistics such as Pearson’s correlation coefficient and multiple regression analysis were used for hypothesis testing. Findings generally support significant relationship between positive psychological capacities and organizational commitment. Manuscript profile -
Open Access Article
314 - Inventory performance evaluation based on demand forecast with Neural Networks (MLP) approach
Yaser TaghinezhadProper management and better control of inventory of food items are one of the most essential and important objectives of food store managers. The store inventory management to improve performance, increase customer service and reduce the deficit in the following days w MoreProper management and better control of inventory of food items are one of the most essential and important objectives of food store managers. The store inventory management to improve performance, increase customer service and reduce the deficit in the following days will be. The purpose of this paper is to provide a prediction model for demanding meat products from Gorgan ETKA chain stores in order to improve inventory performance. In this study, the ANNmlp model has been used to predict the meat market demand of this store and is also compared with ARIMA and 14-day moving average to understand the accuracy of prediction. For this purpose, the code coding of this model was used in MATLAB software and time series data for meat products demand from the beginning of 1392 to the 12th week of 1395, which was received weekly. The results of the research showed that ANN5-8-1 model is the best model for predicting the demand for this product. The prediction model provided by the inventory control period has led to a reduction in the number of days facing the shortage and increased customer service levels. Manuscript profile -
Open Access Article
315 - The effects of psychological capital on organizational trust in the supportive space between staff and management Planning
Qolam Reza Sheisi Reza Khoshcima Mohammad Qafarifard The study on the effect of psychological capital on the relationship between perceived organizational support and organizational trust has been organized among employees who applied research, descriptive and correlational field. Management and Planning Organizati More The study on the effect of psychological capital on the relationship between perceived organizational support and organizational trust has been organized among employees who applied research, descriptive and correlational field. Management and Planning Organization study population consisted of all employees that using Morgan table, 290 individuals were selected as sample. Data analysis was performed using structural equation modeling components of psychological capital as moderator variables moderated the impact of organizational support on organizational trust them. After analyzing the data, it was clear that the increase in each indicator of organizational support, organizational management and planning leads to increased confidence in the organization. The survey results show that all four components of psychological capital has a significant effect on the perceived support and organizational trust. Manuscript profile -
Open Access Article
316 - Studying the effect of factors effective on navigating in in-between spaces of residential complexes based on visual perception (case study: three residential complexes in Kerman)
Firoozeh Azmoon Mahdiyeh Moeini Reza Afhami Abbas MasoudiThe pattern of arrangement of residential blocks regarding the quality of navigation for the residents is one of the most important components in designing residential environments. The reason of studying in-between space is the significance of its design in increasing MoreThe pattern of arrangement of residential blocks regarding the quality of navigation for the residents is one of the most important components in designing residential environments. The reason of studying in-between space is the significance of its design in increasing the residents navigating quality. In some contemporary residential patterns, some of features of in-between spaces have been omitted or, if existing, don’t have an appropriate spatial quality. Navigation in In- between space of the residential environment is of the great importance subject. Significant components are effective in enhancing the optimal quality of routing.Therefore, creating environmental backgrounds has a great significance for increasing the navigating quality in residential settings in-between spaces, since it causes the audiences route readability and as a result raises the spatial quality. This study showed that studying the factors effective on navigating quality from audiences' viewpoint and in the after residence stage may yield effective findings for promotion of planning and design of the residential blocks in-between spaces. After residence evaluation depends on the study of effective factors organization which is the accurate recognition of these factors and their effectiveness in navigating from the residents' viewpoint. In this paper, based on performed studies, the components effective on the audience-oriented navigation were identified and classified in three environmental, human and visual domains. This study evaluates the factors effective in designing in-between space and the relation between them regarding navigation. The history of the subject of the relation of inside and outside space has a close relation with the topics discussed in the domain of environmental psychology and behavioral sciences. The need to such debates in the housing ground and relating to what people want their houses was revealed after the failure of some residential projects constructed in 1950s and 1960s.Comparing the obtained parameters the relations between the components of visual perception may be studied regarding the study's objective. For more clarification of the problem, the objects of the study are mentioned as follows: 1- Finding the factors effective on navigation and environmental perception 2- Finding the relation between the components effective in navigation For finding the environmental-human and visual factors, at first field study of the residential complexes in in-between space was performed, then regarding the studied theoretical fundamentals, a table of these factors was prepared.At first, the mentioned components were scrutinized with the content analysis and then were assessed in three residential complexes with structured observation checklist and questionnaire with 90-person statistical population. The questionnaire was codified in three sections based on the components. Data analysis was performed with the aim of finding the significance and relation of the components with each other with SPSS Version 26 software and using Friedman test. The results of study show that from the residents' perception perspective, the balance between three environmental, visual and human components leads to creation of a more optimal space for navigation. These factors were categorized in three groups. It should be mentioned that the components extraction was performed from the research literature and based on the observational checklist and taking notes. Based on Friedman test, the components priority based on their influence rate according to the findings includes respectively visual component, human component and environmental componentAlso, regarding Freidman test, the environmental variable components in the order of significance includes: Form, stimulus of light, color, knot, sequence, spatial, road, contrast, edge, mark Ranking of human variables of components includes: social liveliness, readability, security, control and supervision, availability, pedestrian orientation Ranking of visual variable components includes environment, area, concentration and compression, centuriation, occlusion This study seeks to prove the balance among environmental, human and visual components and finally suggests the designers of this domain to extract a checklist of all effective items resulting from these three components in pre-residence design and their relation with each other. Also, the relation between these variables was extracted based on triple variables. The result of the study shows that the balance between three components may aid the audience in selecting their path. Also, the results of the study helps the designers for creating a framework based on effective factors to be utilized in pre-residence design due to lack of access to environmental user. Manuscript profile -
Open Access Article
317 - Analyzing the physical components of the interspace and the Biophilic architecture of a residential complex in the metropolis of Isfahan (case example: Zaytoun residential complex)
zohreh pooretesami mahdiye moeini mansoor nikpourBiophilic architecture, which is referred to as biophilic architecture, and the construction of interstitial space in residential complexes in Iran in the current era, is facing many challenges and what is being built;In order to benefit from the principles of biophilic MoreBiophilic architecture, which is referred to as biophilic architecture, and the construction of interstitial space in residential complexes in Iran in the current era, is facing many challenges and what is being built;In order to benefit from the principles of biophilic architecture,which leads to the improvement of the interaction between humans and the environment,it is not considered.At the same time, observing the principles of biophilic architecture(partial interaction between humans and the environment) is one of the most obvious characteristics of improving the architecture of interstitial spaces in the external environments located between the blocks of residential complexes in Iran,which can bring peace of mind and subsequent psychological restoration of the residents. Interstitial space is a space that is constantly It is on the move and not necessarily a place in itself with a built-in boundary. Also,this space becomes a stable place in a geometry with complex inter-relationships, a place where the surrounding geometry inhales and exhales, and the architecture of this space absorbs everything it can use to build it. As the basis of spatial hierarchy, the interstitial space has had a special place in the structure of historical residential architecture in Iran. Nowadays, due to the destruction of the residential architecture structure, the position of the intermediate arena has also suffered from deficiencies. The lack of an intermediate arena has caused many psychological and social anomalies in the structure of today's residential architecture. Meanwhile, unfortunately, nowadays,in the construction of interstitial physical space in neighboring residential environments, we witness the forgetting of the principles and standards of biophilic architecture, which in turn could calm or restore the mentality and spirit of the residents. At the same time, biophilic architecture, which should be induced through creating the body of buildings in residential environments; Remaining unknown and continuous between the natural and building environments, and along with that the interaction between man and nature and the effect of nature on the human psyche, has been damaged and gradually goes into oblivion. Therefore, biophilic architecture can promote the relative understanding of the evolution of the human body and mind and its relationship with nature. However, paying attention to biophilic architecture in the design principles of the interstitial space in general can lead to the improvement of human life. Because the elements of nature, by being placed in the interspace outside the residential blocks, in addition to reducing stress and creating a positive mood in the users, they bring the elements in these spaces closer to each other and thus strengthen the bond between man and nature. Therefore, the aim of the present research is to investigate the interspace in the residential complex of Zeytoun Isfahan based on the approach of bio-oriented architecture. The question is, what is the relationship between the physical components (materials, geometry, height of neighboring buildings and dimensions) of the interspace of Zeytoun in Isfahan city residential complex with bio-oriented architecture from the residents' point of view? Analytical and using the method of logical reasoning along with the method of collecting information in the form of library and field studies with the tool of questionnaire and the use of correlation test came to the conclusion that the physical components of the Biophilic interspace in the residential complex of Zeytoun in the city of Isfahan, (materials, geometry,dimensions,the height of neighboring buildings) in addition to improving the climatic and environmental performance, it has improved the quality of life of the residents and their mental health due to the use of natural systems and processes, and there is a continuous relationship of mutual actions between the physical components of the interspace of the Zeytoun residential complex in the metropolis of Isfahan and Biophilic architecture lies in the direction of improving the relationship between man and the environment, the creation of space and its perception. Also, according to the audience's point of view, the results showed that there is a significant relationship between the physical components (materials, geometry, height of neighboring buildings and the dimensions(length and width)of the interspace with Biophilic architecture from the perspective of the residents in the Zeytoun residential complex with an average significance level of 98%. and the variables have been evaluated positively and in the same direction with each other. Manuscript profile -
Open Access Article
318 - The relationship between Organizational Optimism and Organizational innovation with the mediating role of work Happiness in teachers
Mostafa Alinejhad Abolghasem BarimaniThe purpose of this study was to investigate the relationship between organizational optimism and organizational innovation with the mediating role of work happiness in teachers. The research applied in terms of purpose and method was descriptive, correlation one. The s MoreThe purpose of this study was to investigate the relationship between organizational optimism and organizational innovation with the mediating role of work happiness in teachers. The research applied in terms of purpose and method was descriptive, correlation one. The statistical population of this study included 309 teachers of at the Secondary school of Neka. The statistical sample was 172 participants that determined by the using Krejcie and Morgan table, and selected by stratified random sampling according to gender. Data were gathered by using three of Green et al organizational optimism Questionnaires (2004), Saatchi et al organizational innovation (2010) & Krolof (2007) work happiness Questionnaires. Their reliability was calculated to 0.85, 0.83 and 0.84 respectively by the use of Cronbach Alpha. The collected data was used for analyzed by Structural equation modeling using the partial least squares method (PLS). The results of this study showed that there is a significant relationship between organizational optimism and work happiness with organizational innovation. 46.8% of organizational innovation and 52% of work happiness is explained by organizational optimism. And the work happiness variable has a mediator effect on the relationship between organizational optimism and organizational innovation. Fit indices indicate that the proposed model is an appropriate fit. Manuscript profile -
Open Access Article
319 - The relationship between teacher’s Academic optimism and using active teaching methods in primary schools of Bonab city
Morteza Noor Mohammadgol Mohammadali Mojallal The aim of the research is to explain the relationship between teachers' academic optimism and the use of active teaching methods in primary schools of Bonab city in the academic year 2015-2016. The statistical population is the teachers of primary educatio More The aim of the research is to explain the relationship between teachers' academic optimism and the use of active teaching methods in primary schools of Bonab city in the academic year 2015-2016. The statistical population is the teachers of primary education schools in Benab city, whose number is 489, the statistical sample size is estimated to be 215 using Cochran's formula and selected by stratified random sampling. The data collection tool is Baird and Hoy's academic optimism questionnaire and the researcher-made questionnaire of using active teaching methods, whose reliability was equal to 0.72 and 0.87. Kolmogorov Smirnov test and Pearson correlation test were used to analyze the collected data. The results show that there is a significant relationship between teachers' academic optimism with the use of active teaching methods and all its dimensions (except for the indirect teaching method) in the primary schools of Bonab city. Manuscript profile -
Open Access Article
320 - Evaluation of the four factors affecting the development of a perceived religious identity-building curriculum mediated by individual worldview (Case study: Perspectives of high school teachers in Isfahan)
Mohammadali Salmani Ardani Farhad Shafiepoor Motlagh The aim of this study was to evaluate the factors affecting the development of a perceived religious identity-building curriculum mediated by individual worldview. The statistical universe of present research was consisted of Isfahan city’s all high s More The aim of this study was to evaluate the factors affecting the development of a perceived religious identity-building curriculum mediated by individual worldview. The statistical universe of present research was consisted of Isfahan city’s all high school teachers of Education Department in the academic year of 1392-1393 that number of 340 teachers were selected through the multiphase cluster random sampling method. The present study is applied in terms of purpose and descriptive in terms of method. The data collection tool included 3 researcher-made questionnaires. 1-Effective quadruple values questionnaire (religious, spiritual, moral, human) 2- Personal world view questionnaire in students ‘learning process 3. Questionnaire for developing a perceived religious identity curriculum. To evaluate the reliability Cronbach's alpha was used. Cronbach's alpha of the questionnaires were 0.91 and 0.93 respectively and 0.94 calculated. Factor analysis and construct validity methods were used to evaluate the validity of the questionnaires. Data analysis was performed using SPSS 18 software. The results showed that religious, spiritual and moral values affect the development of perceived religious identity-building curriculum, but the effect of human values on the development of perceived religious identity-building curriculum was not significant. Also, in the fitted corrective model, religious values have a direct effect on the religious identity-building program, both mediated and mediated by an individual worldview. Spiritual and moral values have only a direct effect on the program of perceived religious identity. Human values also indirectly affect the program of religious identity only through the mediation of individual worldview. Manuscript profile -
Open Access Article
321 - The effect of reflective leadership with academic optimism on academic procrastination with the mediating role of feeling of belonging to school
Fereshteh Mohammadi Zahra Tanha Razieh Jalili This research was conducted with the aim of investigating the effect of reflective leadership with academic optimism on procrastination with the mediating role of sense of belonging to the school among the second secondary students of Khorram Abad city. The More This research was conducted with the aim of investigating the effect of reflective leadership with academic optimism on procrastination with the mediating role of sense of belonging to the school among the second secondary students of Khorram Abad city. The descriptive research design was correlational. Sampling of this research was done with the presence of 384 people (235 female, 105 male) using available sampling method among the high school students of Khorramabad city in the academic year of 2021-2022. To measure the variables of the research, the Reflective Leadership Scale in School (SRLS) by Taheri and Taheri (2016), the Academic Optimism Scale (AOS) by Tashanen-Moran et al. (2013), the Academic Procrastination Questionnaire (APQ) by Sawari (2010) and the sense of belonging to school questionnaire (SBSQ) by Brew et al. (2004) were used. Data were analyzed with Pearson's correlation coefficient and structural equations using SPSS and AMOS software version 24. The results showed that there is a significant relationship between school leadership, academic optimism and feeling of belonging to school with procrastination (P<0.01). Also, the results showed that the direct paths of this research were significant and the indirect paths of school leadership and academic optimism were significant through the mediating role of sense of belonging to school on students' academic procrastination. Based on the findings of this research, the final research model had a good fit (RMSEA=0.056 and P-value <0.05). Manuscript profile -
Open Access Article
322 - تحلیل نقادانه گفتمان سیاسی : بررسی چند نمونه ازسخنرانی های نخبگان سیاسی در زبان انگلیسی
بیوک بهنام لاله مقتدیمطالعه حاضرسعی دارد چگونگی کاربرد زبان توسط نخبگان سیاسی در تکوین قدرت را بررسی کند. مقاله با مرور اجمالی بر تحلیل نقادانه گفتمان آغاز می شود و سپس با معرفی مجموعه ای شامل هشت نخبه سیاسی بنام های: مالکوم ایکس - جوزف استالین - نوام چامسکی - ولادیمر لنین - مارتین لوتر کین Moreمطالعه حاضرسعی دارد چگونگی کاربرد زبان توسط نخبگان سیاسی در تکوین قدرت را بررسی کند. مقاله با مرور اجمالی بر تحلیل نقادانه گفتمان آغاز می شود و سپس با معرفی مجموعه ای شامل هشت نخبه سیاسی بنام های: مالکوم ایکس - جوزف استالین - نوام چامسکی - ولادیمر لنین - مارتین لوتر کینگ - وینستون چرچیل - ج. اف. کندی و آدولف هیتلرادامه یافته و سپس سخنرانیها ی نخبگان سیاسی یاد شده با در نظر گرفتن صنایع بدیعی به کار گرفته شده مورد تجزیه و تحلیل قرار می گیرند. سپس داده ها از دیدگاه تحلیل نقادانه گفتمان با استفاده از تئوری سه بعدی مطالعه گفتمان (توصیف - توضیح - تفسیر)- تئوری پیشنهادی نورمن فرکلاف ( 1989)- و تئوری تحلیل نقادانه بافت - پیشنهادی ون دایک( 2004)- مورد کاوش قرار می گیرند. در این تحقیق صتایع بدیعی به شش دسته مهم: قیاس ، گرامر، معنا ، تکرار ، جمله/عبارت معترضه و (فن) بلاغت تقسیم شده اند. نتایج تحلیل آشکار کرد که علیرغم تفاوتها در نوع صنایع بدیعی استفاده شده توسط نخبگان سیاسی انتخاب شده ، الگوی جالب و چشمگیری در گفتمان تمامی افراد انتخاب شده مشترک است و آن عبارت است از استفاده از صنایع گرامر - تکرار و (فن) بلاغت. امید است که این تحقیق دستاوردهای آموزشی ارزشمندی را برای آموزش زبان خارجی در کشور عزیزمان به ارمغان آورد. Manuscript profile -
Open Access Article
323 - Adapting the institution of predictable breach of contract with the extended concept of obligation in the principles of jurisprudence.
Abbas Mirshekari amir javadiThe theory of foreseeable breach of contract refers to a situation in which one of the parties, despite his observations and calculations, cannot reasonably wait for the other party to execute the contract. This theory is relevant in contracts that are subject to a cert MoreThe theory of foreseeable breach of contract refers to a situation in which one of the parties, despite his observations and calculations, cannot reasonably wait for the other party to execute the contract. This theory is relevant in contracts that are subject to a certain period of time. In Iran's legal system, the theory of foreseeable breach of contract is not explicitly accepted, even in certain articles, it is practically not possible to propose such a theory. But since speed and security are one of the main elements in commercial contracts, the design of this theory in Iran's legal system allows the obligor not to wait for the obligee to fulfill his contractual obligations in case of excessive delay, and by planning this type of violation, he can have a suitable time to compensate for the lost time. Although there are obstacles for proposing this theory in every legal system, its acceptance can be much more practical. In the principles of jurisprudence, in a topic entitled extended obligation, it is mentioned to perform the duty within a certain period of time, and the basics of this obligation can be used in the theory of predictable violation. The most important question that we are trying to answer in this article is with what tool the theory of foreseeable violation can be justified in Iran's legal system. By providing this goal, we have progressed from the origin of this theory to its legal analysis. Manuscript profile -
Open Access Article
324 - The Effect of Instruction of Basic Football Techniques on Perceptual-Cognitive Skills in the Field: Emphasizing on Observational and Implicit Learning
Parvaneh Alavinamvar Mohamad Vaez Mmousavi Mehdi NamazizadehThe purpose of this study was to determine the effect of learning some basic soccer techniques on perceptual- cognitive skills on the field. Fifty-eight female participants including 45 students of Azad University of Tabriz branch and 13 skilled soccer club players with MoreThe purpose of this study was to determine the effect of learning some basic soccer techniques on perceptual- cognitive skills on the field. Fifty-eight female participants including 45 students of Azad University of Tabriz branch and 13 skilled soccer club players with a mean age of 22. 30 ± 3.08 years old were selected based on the inclusion criteria and then, were purposefully assigned to five groups [cognitive (near) cognitive (far), control and skilled]. The research method was quasi-experimental studies and its design was pretest-retention. First, a field test was performed on all groups. Then, the acquisition phase for the field group and the practice for the laboratory groups began and finally, after a week, a retention test was performed on the groups. Multivariate analysis of variance test was performed to analyze the data using SPSS 21. The level of anticipation and decision-making skills in the field environment in the motor group and the skilled group was significantly higher than the two groups of laboratory tasks. The results of analysis of covariance revealed that the effect of the group was significant at the level of 99% probability (F (53. 4)) = 12. 77. P = 0.001. Eta coefficient = 50). It seems that, practicing basic skills in combination with observational learning leads to a double engagement of the problem-solving process and improves anticipation and decision-making skills Manuscript profile -
Open Access Article
325 - Effect of Teacher Psychological Empowerment Program on Teacher-Student Interaction, Emotions and Teachers Academic Optimism
mona valeh Omid Shokri Hassan AsadzadehObjective: The purpose of this study was to determine the effect of teacher psychological empowerment training program on Teacher Interaction, emotions and teachers academic optimism. Method: with a quasi-experimental study with a pretest-posttest nonequivalent control- MoreObjective: The purpose of this study was to determine the effect of teacher psychological empowerment training program on Teacher Interaction, emotions and teachers academic optimism. Method: with a quasi-experimental study with a pretest-posttest nonequivalent control-group design and followed by two months, 60 teachers in the experimental groups (30 subjects in experimental group) and (30 subjects in the control group), before and after training, responded to the Questionnaire on Teacher Interaction (QTI), the Teacher Emotion Inventory (TEI), the Teacher Academic Optimism Scale (TAOA). The experimental group received 10 sessions of teachers’ resilience training package (2 hour a session). Results: The results of simple mixed ANOVA indicated that in the short and long term, the psycho-educational package was effective in increasing the psychological capital, teacher positive emotion, teachers’ academic optimism, adaptive dimensions of teacher-student interpersonal relation model and job related positive emotions and in decreasing the teacher negative emotions, job related negative emotions and non-adaptive dimensions of teacher-student interpersonal relation model. Conclusion: In sum, the results of this study according to the theoretical and empirical background of the teacher resilience study area show that in order to achieve the goal of teachers’ psychological capital need to emphasize their psychological psychological empowerment. Teacher psychological empowerment as a comprehensive conceptual framework includes the fields such as relations, motivation and emotions. Therefore, the effort to shape the concept of teacher resilience is made by increasing psychosocial resources. In these situations, on the one hand, teachers’ vulnerability to stressors is reduced, on the other hand, it leads to teacher thriving Manuscript profile -
Open Access Article
326 - The Effectiveness of the Flipped Classroom Teaching Method on the Components of Academic Optimism in Mathematics
Reza Shahi Mahdi Eyvazi Nayyer Heydari KalajehThe important mission of education is to help the all-round development of students intellectually, behaviorally and attitudinally. Academic optimism is considered one of the most important components of attitudinal growth and a complement to the intellectual and behavi MoreThe important mission of education is to help the all-round development of students intellectually, behaviorally and attitudinally. Academic optimism is considered one of the most important components of attitudinal growth and a complement to the intellectual and behavioral growth of students, which has attracted the attention of education specialists and researchers in this field. This research was conducted with the aim of identifying the effect of the flipped classroom teaching method on the components of academic optimism in mathematics. The present research method was semi-experimental with a pre-test-test design with a control group. The statistical population of the research includes all the students of the 6th grade of elementary school in Varzeghan city, firstly, 34 people were selected by the available sampling method, then two experimental groups (17 people) were randomly selected due to the homogeneity of the samples. and control (17 people) were replaced. To collect data, the Academic Optimism Questionnaire (AOQ) of Schennen Moran et al. (2013) was used with a reliability of 0.93 for the whole test. Research hypotheses were analyzed using multivariate analysis of variance method and SPSS26 software. The findings showed that the flipped classroom teaching method significantly increases students' academic optimism in the components of student trust in the teacher (P<0.001), academic emphasis (P=0.013) and school unity (P=0.015). As a result, the flipped classroom teaching method is considered one of the most effective methods of developing academic optimism, which is recommended to sixth grade teachers. Manuscript profile -
Open Access Article
327 - The effectiveness of training the optimism pattern through the storytelling method on increasing school children’s achievement
Hamzeh Ganji Kamran AmirianStorytelling as an indirect method of providing a framework for training and promoting self-understanding, efficiency and unity of experiences, can have an effective role on children and teenagers’ health. Therefore, the aim of the study was the effectiveness of t MoreStorytelling as an indirect method of providing a framework for training and promoting self-understanding, efficiency and unity of experiences, can have an effective role on children and teenagers’ health. Therefore, the aim of the study was the effectiveness of training the optimism pattern through the storytelling method on increasing school children’s academic achievement. The research method was quasi- experimental with experimental and control groups. The pre-test, posttest and follow- up stage were administered. To gather the data academic achievement test scores were used. Using the participants in storytelling workshop, the sample size was randomly chosen among the volunteers who added up to 31 people. Using the pre- test scores, matching group was chosen (experimental 15, control 16). The pre-test was administered 3 months after the completion of 12 treatment sessions and a follow- up test was administered six months after the post- test. Using descriptive and inferential statistics (t- test, ANOVA), the results showed that the mentioned method will increase the children’s academic achievement, it also showed that using this method may eliminate or reduce the other academic achievement problems, too. Manuscript profile -
Open Access Article
328 - The Effect of Capital Productivity Management on Capital Asset Pricing Models with a Focus on Life Cycle
ali alimohammadpour ali zabihi khosro Faghani MakraniCapital productivity concerns the measurement of management power in making optimal use of capital as one of the important and limited company resources. In companies with highly efficient capital productivity, stocks are expected to offer higher returns and the explana MoreCapital productivity concerns the measurement of management power in making optimal use of capital as one of the important and limited company resources. In companies with highly efficient capital productivity, stocks are expected to offer higher returns and the explanatory power of the models proposed to predict stock returns is assumed to increase. The purpose of this study was, thus, to examine the extent to which capital productivity might influence the explanatory power of stock market predictive models and to scrutinize this viable effect at various stages of corporate life cycle. The Operating Profit Ratio (ROIC) was used to operationalize Capital productivity, the Tripartite Factor Model (Fama & Franch, 1993) and the Pentagonal Factor Model (Fama & Franch, 2013) were employed to predict stock returns and corporate life cycle was categorized via the Dickinson Cash Flow (2011). The research sample comprised 110 companies with specific descriptive characteristics selected from among all those listed on the Tehran Stock Exchange during a ten-year period from 2005 to 1394. The results of the hypothesis testing analyses demonstrated that capital productivity affects the relationship between market factor and risk-free growth at all stages of the life cycle, but size was found significantly correlated with risk merely at the maturity stage of the life cycle. Manuscript profile -
Open Access Article
329 - Causal Relationship between Leadership Worldview and Organizational Innovation across Organizational Mindfulness: Administrative Staff at University of Isfahan
seyed hedayatollah davarpanah seyed ali siadat arash yadollahi dehcheshmehThe present descriptive Interrelational research set out to examine causal relationship between leadership worldview and organizational innovation with a focus on the mediating role of organizational mindfulness. The research population included 344 administrative staff MoreThe present descriptive Interrelational research set out to examine causal relationship between leadership worldview and organizational innovation with a focus on the mediating role of organizational mindfulness. The research population included 344 administrative staff at University of Isfahan from 2017-2018. A sample of 182 was randomly selected using the proportional stratified sampling procedure. The researcher data were obtained through a researcher-made questionnaire measuring leadership worldview, the organizational innovation questionnaire and organizational mindfulness questionnaire.The instruments were initially validated and their reliability coefficients were estimated through Cronbach Alpha and found to be 0.88, 0.91 and 0.72, respectively. The collected data were analyzed via SPSS software version 23 and Amos. Results indicated that the revised proposed causal model enjoyed a good fit index and that the research variables could explain 41 and 31 percent of the variance in organizational mindfulness and organizational innovation. Overall, the findings revealed that organizational mindfulness, along with entrepreneurial and network worldviews, had direct significant positive effects on organizational innovation, while the direct effect of communitarian and regulatory worldviews on organizational innovation was found to be insignificant. Moreover, the leadership worldview dimensions were found to have significant positive and direct effect on organizational mindfulness and indirect effect on organizational innovation which is mediated through organizational mindfulness. Manuscript profile -
Open Access Article
330 - Trip Forecasting Process Modeling in Urban Transportation Planning Based on Hybrid Fuzzy Inference Approach
Javad Jassbi Payam MakvandiUrban Transportation Planning (UTP) has been one of the most important decisions in urban planning and development procedures in recent years. Meanwhile, accurate trip forecasting between two given regions of the city could be considered as the key success factor of urb MoreUrban Transportation Planning (UTP) has been one of the most important decisions in urban planning and development procedures in recent years. Meanwhile, accurate trip forecasting between two given regions of the city could be considered as the key success factor of urban transportation planning. Due to the importance of the problem, different models have been developed in the field. The overall problem of trip forecasting and transportation planning could be complicated because of its nature that results from the complicated nature of human behavior. Due to the complexity of the problem, it is always hard to develop forecasting models with acceptable forecasting errors and also low computational expenses particularly in developing countries in which historical data are not fully available. In this paper, a three phase fuzzy model is proposed to forecast trips flow between two given regions of a metropolitan based on mapping demographical and social variables to total number of trips flow. The overall model is to explore the subjective pattern of transportation experts and transfer the subjective model to a mathematical framework. Manuscript profile -
Open Access Article
331 - Improving the Efficiency of Forecasting Productivity, Using a Taguchi Experiment Design Approach (Case Study: Food Industries in Iran)
Seyed mahmon Zanjirchi Mehdi Hatamimanesh Hamedreza Kadkhodazadeh Seyedali MohammadbanifatmiProductivity forecasting is a key factor in strategy planning in an organization. Artificial neural networks method is one of the productivity estimating methods whose users must have enough experience and skill because of its adjustable parameters. Trial and Error is m MoreProductivity forecasting is a key factor in strategy planning in an organization. Artificial neural networks method is one of the productivity estimating methods whose users must have enough experience and skill because of its adjustable parameters. Trial and Error is mostly used to find the proper levels of these parameters. This article presents a seven step pattern for selecting proper adjustable parameters for neural network, using Taguchi experiment design method to improve the efficiency of productivity forecasting. As a result, the optimum parameters levels that lead to the most desirable forecasting in neural network are as follows: the number of hidden layers: 2 layers, the number of neurons in each hidden layer: 7 neurons, learning rate: 0.9 and the number of neural network inputs: productivity indicators with more than 0.85 degree of correlation. Among the above mentioned factors, the number of hidden layers with 71.18% of contribution rate in experiment results is the most important factor in neural network design to forecast the productivity of Iranian food industry. Finally, the overall results of the study showed that using this pattern provides the possibility of choosing competitive strategies besides decreasing forecasting time and cost. Moreover, this pattern helps decision makers with the extent of the consideration that must be put into each adjustable parameter by determining the contribution rate of each parameter in the experiment results. Manuscript profile -
Open Access Article
332 - Predicting Tehran Securities Stock Index By Using Neural Networks
Bita Delnavaz Asghari Mir Feiz FallahshamsThe size and process of the stock price indices are among the most important factors affecting the decisions of the investors in the financial markets. In order to predict the market, different techniques have been used, the most common of which are regression methods a MoreThe size and process of the stock price indices are among the most important factors affecting the decisions of the investors in the financial markets. In order to predict the market, different techniques have been used, the most common of which are regression methods and ARIMA models. However, these models have been unsuccessful in the practical prediction of some series. In the present research, in order to predict the total index of the stock, the Feed Forward Neural Network model with the law of back propagation was used in three networks with different input models, and the results of the model were compared to the result of multi – variable regression models and ARIMA models. The results indicated that the neural network method showed considerably fewer RMSE errors than RMSE errors in other methods, and that in Tehran stock market short – term prediction within a shorter interval is more suitable than long – term prediction within a longer interval. Manuscript profile -
Open Access Article
333 - Analysis and prediction of water level fluctuations in Urmia Lake using ARIMA model
khadijeh javan Farhad NasiriThis study has been done to evaluate the fluctuations of water level in Urmia Lake and to provide a best model for prediction the water level fluctuations. Monthly water level data for the period (1345 - 1392) was used and homogeneity was assessed by Run Test. Then the MoreThis study has been done to evaluate the fluctuations of water level in Urmia Lake and to provide a best model for prediction the water level fluctuations. Monthly water level data for the period (1345 - 1392) was used and homogeneity was assessed by Run Test. Then the stability of mean and variance of the data was tested in order to put down the non-stability by creation a rank in series. Trend of the monthly series was eliminated by making a difference and the time series of water level was evaluated by using Box- Jenkins model and the best model was fitted. Accuracy of the model was verified based on AIC, BIC and chart analysis of autocorrelation and partial autocorrelation functions and ARIMA = (0, 1, 4) (1, 1, 1)12 was selected as a suitable model. The selected model was fitted then the model was tested by Analysis of residuals and confirmed its authenticity. Finally, the monthly behavior of the series was predicted for 9 years later by using this model. Manuscript profile -
Open Access Article
334 - Study and Evaluation of Temperature in Aleshtar City based on Artificial Neural Network Model
Mahnaz Hassanvand Reza Borna Manijeh Zohoorian Pordel Alireza ShakibaTemperature assessment and forecasting is one of the most practical estimates of climatic elements. Today, the agricultural and industrial sectors are highly dependent on the temperature conditions. Temperature is one of the most important climatic meters that is one of MoreTemperature assessment and forecasting is one of the most practical estimates of climatic elements. Today, the agricultural and industrial sectors are highly dependent on the temperature conditions. Temperature is one of the most important climatic meters that is one of the main factors in the climate identity of each region. The purpose of this study is to make a model for predicting the average monthly seasonal temperature of selected stations in Lorestan province, including Al-Shatrami region. Identification and detection of vulnerabilities in the infrastructure of Aleshtar districts in the conditions of climate change. And due to the inadequacy of the 30-year time series of Al-Ashtarl, neighboring cities such as Khorramabad-Aleshtar-Borujerd synoptic stations have been used, because the artificial neural network method has a great ability to simulate and predict atmospheric elements. And the weather, especially the temperature. To model and predict the seasonal monthly temperature, the r programming tool software of the fOre gast package has been used. Two tests of estimator trend analysis have been used. The 30-year time series trend of these elements was examined during the basic statistical period (1989-2019). The climate cycle was reported and extracted under two scenarios: NNAR and forEgast. The artificial neural network is one of the most powerful models capable of receiving and displaying complex Data input and output is one of the most widely used neural network (NNA) models to determine the best network inputs. Manuscript profile -
Open Access Article
335 - Simulating and predicting the effects of climate change using some new scenarios of SSP and CMIP6 models on rainfall changes in Ardabil County
Bromand Salahi Mahnaz Saber Fatemeh Vatanparast Ghaleh JuqIn this research, the annual rainfall changes of Ardabil City have been modeled and analyzed based on the downscaling of the output of some CMIP6 models under the greenhouse gas emission scenarios in the SDSM6.1 software. For this purpose, the daily precipitation of the MoreIn this research, the annual rainfall changes of Ardabil City have been modeled and analyzed based on the downscaling of the output of some CMIP6 models under the greenhouse gas emission scenarios in the SDSM6.1 software. For this purpose, the daily precipitation of the Ardabil synoptic station from 1979 to 2014 was considered as observational data, and its changes were analyzed for the next decades until 2043. The downscaled results in the base period under CanESM5 and NorESM2-MM general circulation models showed relatively good performance in estimating the monthly precipitation of Ardabil station. The results showed that in March, April, and May, there is an underestimation, in July there is an overestimation and in the other months there is a relatively good performance with the observational data. The annual average precipitation of the future period based on the output of the CanESM5 model under the SSP1-2.6 and SSP5-8.5 scenarios was calculated as 245 and 243 mm respectively, which shows a decrease of about 38 and 40 mm compared to the average of the historical period. The results of the Ardabil rainfall simulation with the CanESM5 model showed that on a monthly scale, the rainfall in the next 20 years in April and May under the SSP1-2.6 scenario is between 14 and 15 mm and under the SSP5-8.5 scenario between 16 and 17 mm will decrease and in July to September and December, it will increase by at least 5 mm compared to the base period. Manuscript profile -
Open Access Article
336 - مدیریت بحران با تاکید بر مخاطرت طبیعی و پیش بینی احتمال وقوع خشکسالی استان کرمانشاه در محیط GIS
نادر پروین سارا کوشکی زمانی سیروس حسن پور هایده کیانی آلرد -
Open Access Article
337 - پیش بینی و تحلیل امواج گرمایی شهر زنجان با استفاده از ریزگردان لارس دبلیو جی و شاخص بالدی
Broumand Salahi زینب قدرتیموج­های گرمایی یکی از مهمترین بلایای آب و هوایی است که پیامدهای زیستمحیطی را بر طبیعت بر جای می­گذارند. هدف اصلی پژوهش، پیش­بینی امواج گرمایی شهرستان زنجان در دو بازه­ی زمانی 1390-1409 و 1425-1444 توسط نرمافزار LARS-WG با دو مدل HadCM3 و BCM2 و با سنا Moreموج­های گرمایی یکی از مهمترین بلایای آب و هوایی است که پیامدهای زیستمحیطی را بر طبیعت بر جای می­گذارند. هدف اصلی پژوهش، پیش­بینی امواج گرمایی شهرستان زنجان در دو بازه­ی زمانی 1390-1409 و 1425-1444 توسط نرمافزار LARS-WG با دو مدل HadCM3 و BCM2 و با سناریوی A1B است. پس از آمادهسازی و کنترل کیفی، داده­ها بهصورت روزانه وارد نرمافزار LARS-WG شدند و خروجی مدل پس از صحت سنجی توسط روش­های آماری، برای تحلیل موج گرمایی با استفاده از شاخص بالدی آماده شد. نتایج پژوهش نشان داد که بر اساس مقادیر R2، RMSE، MAE و آزمون کولموگروف اسمیرنوف، شبیه­سازی­های صورت گرفته در ایستگاه مورد مطالعه از دقت قابل قبولی برخوردارند. نتایج پژوهش همچنین نشان داد که در شهر زنجان بر اساس دو مدلBCM2 و HadCM3، موج کوتاه گرمایی در هر دو بازه روند افزایشی داشته است. بیشترین فراوانی موج کوتاه گرمایی در بازه زمانی اول در ماههای خرداد و تیر قرار دارد و در بازه زمانی دوم، فراوانیامواجکوتاهگرماییدر ماههایفروردینواردیبهشتبیشتر شدهودرنتیجهباتوجهبهپیشبینیانجامگرفتهدرهردومدل،برتعدادروزهایگرمافزودهمیشود.براساسپیشبینیانجامشدهبراساسمدل BCM2،طولدورهگرمدرایستگاهموردمطالعهدرحالافزایشاستوماه­هایخنکفصلبهاربهتدریجبهسمتگرمترشدنپیشمیروند. با توجه به پیش­بینی انجامشدهبراساسمدل BCM2، احتمال جابه­جایی فصول در این ایستگاه­ در سالهای آینده وجود دارد و بهتدریج فصل بهار به لحاظ ویژگی­های اقلیمی به فصل تابستان شباهت زیادی پیدا خواهد کرد. با توجه به پیش­بینی انجامشدهبراساسمدل HadCM3، موج کوتاه گرمایی در بازه زمانی اول روند افزایشی تندتری نسبت به بازه­ی زمانی دوم دارد و دردورهزمانیدوم،تغییراتفراوانیامواجگرماییکوتاهبیشتراستودرکل،روندافزایشیدمایایستگاهسینوپتیکزنجانراتأییدمیکند Manuscript profile -
Open Access Article
338 - Assessment of NARX Neural Network in Prediction of Daily Precipitation in Kerman Province
Kamal Omidvar Maasomeh Nabavizadeh Meysam SamarehghasemPrecipitation is one of important parameters of climatology and atmospheric science that have more importance in human life. recently, extensive flood and drought entered many damage to most parts of the world. Precipitation forecasting has important role in management MorePrecipitation is one of important parameters of climatology and atmospheric science that have more importance in human life. recently, extensive flood and drought entered many damage to most parts of the world. Precipitation forecasting has important role in management and warning of this problem. Due to the interaction of various meteorological parameters in the calculation of rain, leads it to a very irregular and chaotic process. The purpose of this study, assessment of forecasting precipitation, using data from meteorological stations of the using common statistical period (2012-1989) in Kerman, Baft, Miandeh Jiroft. In this way, to the training of the artificial neural networks with structure Perceptron, Nonlinear Autoregressive External. Effective Factors in the rain, as input for Artificial Neural Networks and precipitation was considered as the output of the Network. Statistic indicators MSE, R were used for performance evaluation of the models. The analysis of output results from, Nonlinear Autoregressive External Neural Networks shown that these models have better accuracy and a high ability to forecast precipitation than Perceptron Neural Networks. The results showed the more exact method concerned to the (NARX) model. The 42 models with all parameters with Levenberg Marquat rule and sigmoid function had the best topology of the model in three stations. Overall, evaluation of NARX results showed that the errors of ANN were negligible. The NARX showed high sensitivity to relative humidity. Manuscript profile -
Open Access Article
339 - پیش بینی دمای کمینه ایستگاه کرج با استفاده از داده های شاخص های پیوند از دور و شبکه عصبی مصنوعی
هانیه شکیبا محمود خسروی تقی طاووسی مهدی اژدری مقدمتوجه علمی به مخاطرات محیطی که آسیب پذیری بسیاری از کشورهای دنیا را به دنبال دارد، آغازی نسبتاً تازه دارد. یکی از این خطرها یخبندانها می باشند که سبب زیانهای عظیمی در زمینه های کشاورزی، حمل و نقل، انرژی ، زیست محیطی و غیره شده است. جهت جلوگیری از خطرات ناشی از آنها استفا Moreتوجه علمی به مخاطرات محیطی که آسیب پذیری بسیاری از کشورهای دنیا را به دنبال دارد، آغازی نسبتاً تازه دارد. یکی از این خطرها یخبندانها می باشند که سبب زیانهای عظیمی در زمینه های کشاورزی، حمل و نقل، انرژی ، زیست محیطی و غیره شده است. جهت جلوگیری از خطرات ناشی از آنها استفاده از روشهای پیش بینی امکان پیش آگاهی از حداقل دما و رخداد پدیده یخبندان را فراهم ساخته تا مسئولان در جهت جلوگیری از آن، اقدامات لازم را به عمل آورند. پیش بینی حداقل دما در منطقه خصوصاً با روشهای جدید از ضروریات انجام این تحقیق می باشد. با توجه به محدودیت هایی از قبیل عدم کفایت آمار موجود و خطای بالای روش های آماری معمول، در این تحقیق از شبکه های عصبی مصنوعی به عنوان یک روش کارآمد جهت پیش بینی کمینه دما استفاده شدهاست. ورودی مدل،آمار شاخص های اقلیمی SIBERIA, AO[1], NAO[2], TNA[3], SOI[4], PDO[5], TNI[6], NOI[7]ساعات آفتابی منطقه در بازه زمانی(2007–1973) و خروجی مدل داده های کمینه دما می باشد. در این تحقیق از دو روش پس انتشار feedforwardو Radial Basisاستفاده شده است. نتایج نشان داد که بین مدلهای مورد استفاده، Radial Basis ( با ضریب همبستگی 98% و میزان خطای 48%) به عنوان بهترین مدل، نسبت به روش های آماری و مدل feedforward معمول می باشد و همچنین نسبت به دیگر تحقیقات انجام شده در این زمینه از میزان خطای پایین تری برخوردار است. همچنین تنها افزایش فاکتورهای ورودی شبکه عاملی برای افزایش کارایی نمی باشد بلکه استفاده از ورودی هایی که ارتباط معناداری با خروجی شبکه دارند نتایج بهتری را ایجاد خواهد کرد. در نهایت خروجی مدل بیانگر افزایش حداقل دما طی دوره آماری می باشد. Manuscript profile -
Open Access Article
340 - پیش بینی نوسانات اقلیمی برای سه دهه؛ مطالعۀ موردی: استان مازندران
مهرداد رمضانی ‏پوردر دهه‏های اخیر،نوسانات اقلیمی به عنوان تهدید به شمار می‏رود.در این راستا نوسانات پارامترهایبارندگی، دما و تابش، بر پایۀدوره آماری 2009-1995 برای سه دهه (2039-2010) برایبخش‏های شرقی، مرکزی و غربی استان مازندران از طریق مدلLars-WG،مدل‏سازی و تحلیل گردید. Moreدر دهه‏های اخیر،نوسانات اقلیمی به عنوان تهدید به شمار می‏رود.در این راستا نوسانات پارامترهایبارندگی، دما و تابش، بر پایۀدوره آماری 2009-1995 برای سه دهه (2039-2010) برایبخش‏های شرقی، مرکزی و غربی استان مازندران از طریق مدلLars-WG،مدل‏سازی و تحلیل گردید. ابتدا با انطباق منطقی داده‏های تولیدشده و داده‏های دیدبانی‏شده، مدل Lars-WG صحت‏سنجی شد و نهایتاً بر اساس مدلمذکور، روند تغییرات اقلیمیمناطق تحقیقبرایدورۀ آماری2039-2010 پیش‏بینی گردید. نتایج پژوهش نشان داد که دمای حداقلدر منطقۀغرب، مرکز و شرق استانمازندران روند افزایشی و دمای حداکثردر مناطق غرب و شرق، روند کاهشی و در منطقۀ مرکزی، روند افزایشی خواهد داشت. مجموع بارندگی سالانه در منطقۀ غرب با روند افزایشی و در مناطق مرکزی و شرقی با روند کاهشی مواجه خواهد بود. همچنین ساعات آفتابی در مناطق غرب و شرق استانمازندران،روند کاهشی و در منطقۀمرکزی، روند افزایشی خواهد داشت. Manuscript profile -
Open Access Article
341 - Subject: Forecasting Occurrence of Radiation Frost withmeteorologicalMinimum Data, Case Study :Shahroud(Semnan Province)
Gholamreza JanbazghobadiFrost is one of the major climatic Hazards that creates irreparable damages in various communities every year. Amongst different kinds of frosts, radiation frost is very important; because of frequency occurrence and iscontrollable well with active protectio MoreFrost is one of the major climatic Hazards that creates irreparable damages in various communities every year. Amongst different kinds of frosts, radiation frost is very important; because of frequency occurrence and iscontrollable well with active protection methods in agricultural sector. Along with radiation frost monitoring,Precise forecasting of the minimum temperature and hourly estimation of its variations (trend) during the nights with frost event for starting and ending time determination of the active protection methods is satisfied.Therefore, using an experimental forecasting model, which can calibrate to meet local conditions and have a simple application, it seems essential. Thereafter, this study aimed at predicting the minimum temperature using a Polynomial model. In this paper, using hourly synoptic data of shahroud station for January, February during 1984-2010, dry temperature after sunset embedded for developing the prediction model of minimum temperature. Then, according to the predicted minimum temperature, the temperature trend during the night hours with radiation frost event was incident prediction., Pearson correlation coefficient value between observed and predicted minimum temperatures based on developed model was In the significant confidence level of high. The amount of root mean square error (RMSE) for the developed model is 0.2 °C for January. Manuscript profile -
Open Access Article
342 - پیشبینی سرمای دیررس بهاره با استفاده از شبکهی عصبی پرسپترون چند لایه (MLP) و تاثیر آن در حمل و نقل شهر خرمآباد
Saeid Taghavi Haniyeh Omidzadeh -
Open Access Article
343 - The mediating role of leader-member exchange and organizational identification in the relationship between ethical leadership and organizational cynicism
marzieh heydari leila sharifiThe aim of this study was to investigate the mediating role of leader-member exchange and organizational identification in the relationship between ethical leadership and organizational cynicism of school teachers in Abadeh. This research is descriptive and correlationa MoreThe aim of this study was to investigate the mediating role of leader-member exchange and organizational identification in the relationship between ethical leadership and organizational cynicism of school teachers in Abadeh. This research is descriptive and correlational in terms of applied purpose, research method and the statistical population of this research consists of school teachers in Abadeh, whose number is equal to 1274 people. To select the sample size using the Cochran's formula, a sample of 295 people was selected by stratified random proportion or volume. To measure organizational cynicism from Kalagan Questionnaire (2009); Organizational identification (Boyle et al., 2019); Emadifar ethical Leadership (2009); Leadership member exchange (Ebrahimkhah, 2014) was used. The reliability of the questionnaire was evaluated by Cronbach's alpha coefficient and its composite reliability and validity were evaluated by construct and content validity. The research hypotheses were analyzed using structural equation modeling technique. The results showed that ethical leadership has a positive and significant effect on organizational cynicism. Leader exchange and organizational identification also mediate the relationship between ethical leadership and organizational cynicism. Manuscript profile -
Open Access Article
344 - The Effects of Money Market on Gold Market with a Systemic Dynamics Approach
fatemeh khani Ahmad Jafari Samimi amirmansor tehranchian mohammdali ehsaniAbstract The purpose of this paper is to apply the system dynamics approach to forecasting the price of gold in Iran, identify the factors affecting the price of gold and simulate the trend of the impact of monetary policy on the price of gold in the period 1405-2010. MoreAbstract The purpose of this paper is to apply the system dynamics approach to forecasting the price of gold in Iran, identify the factors affecting the price of gold and simulate the trend of the impact of monetary policy on the price of gold in the period 1405-2010. The simulation is performed with Wenzim software. In different scenarios, the present paper simulates the change in liquidity volume, consumer price index and bank interest rates on the gold market. The results show that the price of gold is not only affected by the global ounce price and the value of the dollar, but also the control of liquidity and curbing inflation will play a significant role in stabilizing the gold market. The results confirm that the volume of liquidity and the consumer price index have a direct impact and a significant role in increasing the price of gold. The findings also show that changes in bank interest rates have no effect on changes in gold prices. Manuscript profile -
Open Access Article
345 - An Empirical Examination of Stability, Predictability and Volatility for Capital Markets in Persian Gulf Rim
yadollah Dadgar Behzad VamaziariThis paper examines the dynamic relationship of stock markets, stability, predictability, volatility, and persistence of shocks volatility of stock markets in Iran, Saudi Arabia, United Arabic Emirates, Qatar, Bahrain and Oman. In this paper, Generalized Autoregressive MoreThis paper examines the dynamic relationship of stock markets, stability, predictability, volatility, and persistence of shocks volatility of stock markets in Iran, Saudi Arabia, United Arabic Emirates, Qatar, Bahrain and Oman. In this paper, Generalized Autoregressive Conditional Heteroskedasticity model (GARCH) and Autoregressive Moving Average model (ARMA) are implemented by using monthly data during 1990-2010. The results indicate that stock market doesn’t have notable predictability in Iran and there is Cluster volatility for return of stock in most markets and almost, in none of these markets except Oman, explosive volatilities are observed. It is also indicated that the return for markets of Bahrain and Oman doesn’t have stability in significant level of 5 percent and for Iran it doesn’t have stability and durability in significant level of 1 percent. In addition, although the markets of these countries have high capacities for return of investment, but, in particular, the findings show a low correlation between these markets. Also, the results for the period in question explain that none of these markets has the ability of leadership among others. Manuscript profile -
Open Access Article
346 - Comparing the Performance of ARIMA and MS-AR Models to Forecast Business Cycles in Iran
Mehdi Fazel Akbar Tavakoli Mostafa RajabiIt is clear that business cycles are inevitable in economy. On the other hand, the economists are always looking for how to form business cycles and so under the effect of economic policies, since the economic situation is depended to these policies. Therefore, the acce MoreIt is clear that business cycles are inevitable in economy. On the other hand, the economists are always looking for how to form business cycles and so under the effect of economic policies, since the economic situation is depended to these policies. Therefore, the access to more precise business cycles forecasting methods would direct and manage the economic situation and policies powerfully. Hence, the main objective of this study is to construct a new model based on Markov-Switching Autoregressive (MS-AR) model to forecast the business cycles in Iran. In addition, the model constructed is compared to ARIMA to represent its power. GDP data seasonally covers the period 1989: I – 2009: IV collected from Central Bank of Iran. MS-AR and ARIMA models are applied to forecast the behavior of business cycles. By using MAPE, RMSE and Theil criteria (TIC), the results indicate that MS-AR model will work better than ARIMA to forecast GDP business cycles. Manuscript profile -
Open Access Article
347 - Forecasting OPEC Crude Oil Price by Applying Gray Forecasting Model
H. Javanmard S. F faghidianIn world economy, crude oil is considered as one of the most strategic commodities playing a vital role in the determination of many regional and global equations. So, it is well known that an intense fluctuation of the oil price causes large recession in OPEC countries MoreIn world economy, crude oil is considered as one of the most strategic commodities playing a vital role in the determination of many regional and global equations. So, it is well known that an intense fluctuation of the oil price causes large recession in OPEC countries. So many researchers attempt to forecast crude oil price while oil market is one of the most complex, turbulent and chaotic international financial markets. In present research, gray system theory is utilized to model and forecast the price of crude oil. The results represent that gray forecasting model significantly improves the accuracy of the forecasting operation. Manuscript profile -
Open Access Article
348 - Expansion of Financial Distress Modeling Using Corporate Earnings Management in the Iran's Economic Environment
Abbas Ramezanzadeh Zeidi Khosro Faghani Makrani Ali jafariThe purpose of this study is to provide a model for financial distress predicting with real earnings management.So the redesignthe financial distress prediction model of Altman (1983) with the real earnings management variable as a predictor variable, the performance of MoreThe purpose of this study is to provide a model for financial distress predicting with real earnings management.So the redesignthe financial distress prediction model of Altman (1983) with the real earnings management variable as a predictor variable, the performance of the unadjusted model and the adjusted model in predicting of financial distress among companies accepted in the Tehran Stock Exchange was compared.The statistical sample consists of 179 Companies during the years 2008- 2017.Data analysis and hypothesis testing were performed using multiple logistic regression.The results show that the overall accuracy of the adjusted model is higher than the unadjusted model. Manuscript profile -
Open Access Article
349 - Stock Price Forecasting through Using ANN and ARIMA Techniques: A Case Study of Pars Petroleum Company
Seyed Nezame aldin Makian Fateme sadat MousaviStock exchange market is one of the important ways to investment. In this market, the investors are looking for the best securities to maximize the profit. Therefore, forecasting the stock price of next day has a vital role in purchasing such securities. To do this, app MoreStock exchange market is one of the important ways to investment. In this market, the investors are looking for the best securities to maximize the profit. Therefore, forecasting the stock price of next day has a vital role in purchasing such securities. To do this, application of Neural Networks financial forecasting has become very popular over the last few years. In this paper, for predicting the next day's close stock price of Pars Petroleum Company, Artificial Neural Network (ANN) and Autoregressive Integrated Moving Average (ARIMA) will be developed, used and compared. The data are daily collected and analyzed during 2009-2011. The findings indicate that forecasting the price by Neural Network is superior to ARIMA due to its less error coefficients and high explanatory ability. Manuscript profile -
Open Access Article
350 - Analytical review of Turkish laments of Shahriyar
mehdi ramazani shirzad tayefi Elegy can be considered as a type of world literature in which the content of all nations, common humanity and its history along the life is long. In the elegy, the poet says of his own emotions, the nature of the lyric literature, the spirit, and terms of the poe More Elegy can be considered as a type of world literature in which the content of all nations, common humanity and its history along the life is long. In the elegy, the poet says of his own emotions, the nature of the lyric literature, the spirit, and terms of the poet's life are affected severely. In the context of General Turkish lyrics of Shahriyar, there are several subjects, among them are elegies and laments with high frequency. General Turkish lyrics of Shahriyar are tried to precise readout and utilize inductive method. we analyzed all of his tragedy. Among the reasons for the frequency of Lamentations, we can refer to an emotional breakdown, love of family, friends' plurality and diversity, the question of requiem others, dilution nature, scope and pointed of his poetry. Manuscript profile -
Open Access Article
351 - پیش بینی دمای سطح سنگزنی خزشی با استفاده از منطق فازی و به کمک روش هدایت حرارتی معکوس (IHCP)
محمد صدیقی علیرضا بابائی داود افشاری -
Open Access Article
352 - Investing Neural Network Trianing with Metaheuristic Algorithms in order to Prediction of Iran Stock Index
Seyed Ahmad Mirzaei Zakiyeh Nikdel Zahra NikdelPrediction and analysis of stock market movements are an important topic for researchers, traders and have got an important role in today’s economy. Variety in policies, such as government policies and economic policies affect the stock market and cause stock pric MorePrediction and analysis of stock market movements are an important topic for researchers, traders and have got an important role in today’s economy. Variety in policies, such as government policies and economic policies affect the stock market and cause stock price changes. The predicting stock price movement on a daily basis due to the non-linear and chaotic stock price movements is a difficult task. There are several ways for predicting in stock market. Artificial intelligence techniques have been widely used to predict data with nonlinear and chaotic structure. One of these techniques is neural network. If neural network is trained correctly, then it has minimum error in predicting. In this research, we will train the multi layer perceptron neural network with 8 meta heuristics algorithms and we predict Tehran Exchange Dividend Price Index (TEDPIX). The Results show that grey wolf optimization has the minimum error in training of neural network. Manuscript profile -
Open Access Article
353 - Designing a model for predicting the financial bankruptcy of companies listed in the Tehran Stock Exchange using artificial neural networks and comparing it with the logit regression model
farhad sanchooliConsidering the concerns that investors have about the return of principal and capital gains and the consequences and costs that bankruptcy can cause for companies and the country's economy and other individuals and institutions, the design of a reliable model In order MoreConsidering the concerns that investors have about the return of principal and capital gains and the consequences and costs that bankruptcy can cause for companies and the country's economy and other individuals and institutions, the design of a reliable model In order to predict the probability of bankruptcy of companies, it seems necessary to guide decision makers such as investment companies, banks and the government.In this research, the artificial neural network method and the logit regression method were used to predict the bankruptcy of a number of companies admitted to the Tehran Stock Exchange during the years 2015 to 2019, and the results were compared with the logit regression method. The overall prediction accuracy of the artificial neural network method for each of the years t, t-1, t-2 and t-3 is equal to 96.55%, 96.55%, 92.24% and 24/2 respectively. 92% and for the logit regression method for the same years, it is 94%, 94.82%, 90.51% and 87.06% respectively, which showed that the artificial neural network method has a higher accuracy than the logit regression method. is. Therefore, it can be concluded that the artificial neural network method provides a more appropriate tool for predicting the bankruptcy of companies. Manuscript profile -
Open Access Article
354 - Forecasting Future Trends of the Stock Market Using the Probit Regression Approach with Emphasis on Value at Risk
Seyed Ali Mousavi Loleti Emran Mohammadi Saeed ShavvalpourForecasting has always been recognized as an important issue in financial markets and is considered a unique factor in estimating future unknown values. The aim of this research is to identify and forecast the conditions of the Tehran Stock Exchange(TSE) and the factors MoreForecasting has always been recognized as an important issue in financial markets and is considered a unique factor in estimating future unknown values. The aim of this research is to identify and forecast the conditions of the Tehran Stock Exchange(TSE) and the factors affecting them, focusing on the correlation between market prosperity and value at risk. To achieve this, in the first step of this study, the time series of the value at risk index on the capital market TSE was estimated using daily data and the first-order GARCH method from spring 2010 to June 2023. Then, the factors influencing prosperity in TSE were evaluated based on seasonal data from spring 2010 to June 2023 using the probit regression approach. In addition, value at risk index was calculated seasonally and the relationship between the probability of market prosperity and the value at risk index was examined using correlation coefficients.The research results show that the probability of market prosperity in the Iranian capital market has a significant negative relationship with the bank interest rate, liquidity growth and the occurrence of sanctions. There is also a significant positive relationship with the inflation rate and the growth of the exchange rate. Furthermore, the correlation analysis shows that market prosperity is directly related to equity value at risk. Assuming stable conditions, the research suggests that the probability of a prosperity market in the next three seasons is significantly higher than the occurrence of a recession. Manuscript profile -
Open Access Article
355 - An Intelligent Method for Death Prediction Using Patient Age and Bleeding Volume on CT scan
Yosra Azizi Nasrabadi Ali Jamali Nazari Hamid Ghadiri Farshid Babapour MofradThe purpose of this paper's prediction of survival or death within 30 days is based on a cerebral hemorrhage. Timely and correct diagnosis and treatment of cerebral hemorrhage are essential. If the patient's death is predicted during these thirty days, the treating phys MoreThe purpose of this paper's prediction of survival or death within 30 days is based on a cerebral hemorrhage. Timely and correct diagnosis and treatment of cerebral hemorrhage are essential. If the patient's death is predicted during these thirty days, the treating physician should use intensive care and more treatment for the patient. Cerebral hemorrhages require immediate treatment and rapid and accurate diagnosis. In this article, using the volume of cerebral hemorrhage and the patient's age and using the neural network of support vector machine (SVM), it is predicted what percentage of people with cerebral hemorrhage survive and what percentage die. Parameters of cerebral hemorrhage volume and, age of patients, neural network input are considered. The network's output is the survival or death of patients with cerebral hemorrhage over the next thirty days. The data we used included the bleeding volume and age of 66 patients with lobar hemorrhage, 76 patients with deep bleeding, nine patients with Pontine hemorrhage and 11 patients with cerebellar hemorrhage. All bleeding models are considered as input to the support vector machine neural network. The overall accuracy of the designed support vector machine neural network is 93%. Regardless of the type of cerebral hemorrhage, the survival or death of people with cerebral hemorrhage within 30 days is predicted. Manuscript profile -
Open Access Article
356 - A Feature Extraction Based Long-Term Electricity load forecasting Framework to Reduce the Outliers Data Effects
Mohammad Davoud Saeidi Majid MoazzamiElectrical load forecasting is the prediction of future demands based on various data and factors containing different consumptions on weekdays, electricity prices and weather conditions that are different for societies and places. Generally, medium-term electrical load MoreElectrical load forecasting is the prediction of future demands based on various data and factors containing different consumptions on weekdays, electricity prices and weather conditions that are different for societies and places. Generally, medium-term electrical load forecasting is often used for the operation of thermal and hydropower plants, optimal time planning for maintenance of power plants and the power grids. However, long-term electrical load forecasting is used to manage on-time future demands and generation, transmission and distribution expansion planning. In this paper, a hybrid long-term load forecasting approach using wavelet transform and an outlier robust extreme learning machine is proposed. Hourly load and temperature data were extracted from the GEFCOM 2014 database and divided into two classes of training and test. The one-level wavelet transform is used to decompose data to extract properties and reduce the dimensions of the data matrix. Decomposed low-frequency component (approximations) and high-frequency component values (details) from wavelet analysis are entered into the model for training and forecasting. For comparison accuracy of the proposed method, wavelet transform is applied to the data for the other three extreme learning machines. Also data without wavelet transform entered into four other forecasting models and the load forecasting results are compared with the proposed method. The results of the above mentioned evaluation show that electrical load forecasting by using wavelet transform and outlier robust extreme learning machine improves forecasting accuracy and the MAPE reduces to 3.0966. The overall calculated error by the proposed method was the best result obtained between the three several models of extreme learning machines and without preprocessing model. The MAPE is 0.4208 less than the ELM, 0.944 less than the RELM, and 0.1353 less than the WRELM model, respectively. Manuscript profile -
Open Access Article
357 - Electricity load forecasting using hybrid models based on Multi-Layer Perceptrons Neural Network and Seasonal Auto-Regressive Integrated Moving Average models
Fateme Chahkoutahi Mehdi KhasheiNowadays, saving time and economy of each country requires proper planning, decision making, and rational forecasts in different areas. One of the most well-known areas that has received a lot of attention is electricity forecasting. The features of the electricity whic MoreNowadays, saving time and economy of each country requires proper planning, decision making, and rational forecasts in different areas. One of the most well-known areas that has received a lot of attention is electricity forecasting. The features of the electricity which makes it distinguished from other commodities are the impossibility of storing it and the existence of seasonality and nonlinear and ambiguity pattern in electricity data set. These features of the electricity makes it more difficult to forecast using traditional methods. Therefore, in this paper, a parallel optimal hybrid model using seasonal linear and nonlinear methods is proposed to forecast the electricity load forecasting. The main idea of this model is the use of the advantages of individual models in the modeling of complex systems in a structure, simultaneously. Experimental results indicate that in this method due to the use of a direct weighting method, the computational cost of modeling it is significantly lower than other parallel hybrid methods. Manuscript profile -
Open Access Article
358 - Long-Term Demand Forecasting in Electrical Energy Supply Chain of Espidan Ironstone Industry using Deep Learning and Extreme Learning Machine
Sepehr Moalem Roya M. Ahari Ghazanfar Shahgholian Majid Moazzami Seyed Mohammad KazemiEspidan ironstone industries is one of the most consumed power industries in the electricity supply chain of Isfahan province as the second industrial hub of the country and one of the main suppliers of raw materials in the supply chain of the country's steel industry. MoreEspidan ironstone industries is one of the most consumed power industries in the electricity supply chain of Isfahan province as the second industrial hub of the country and one of the main suppliers of raw materials in the supply chain of the country's steel industry. Planning in a large-scale electricity supply chain, in a space full of uncertainty, is begin with electricity demand forecasting.In this paper, a hybrid long-term demand forecasting method in the electricity supply chain of Isfahan's ironstone industries using a combined data mining method including wavelet transform,deep learning and intensive learning machine is proposed. The used data in this study is according to the recorded information from the electrical energy demand signal of Espidan ironstone industries in a period of 40 months in the form of 24-hours. The data in a part of the study period due to the lack of production of this industry in some hours are interrupted. So that only 40% of the data had a value and the remaining, 60% were zero. This subject led to information deficiencies and increases the forecasting error up to 40% in the first step of the proposed algorithm. By completing the first step of the proposed model with intense learning machine (ELM) the forecasting error is reduced and it was possible to create an improved forecasting model for supervised training. Finally, simulation results are compared with other available approaches such as support vector machine and decision tree. The results show the improvement and reduction of error and a significant increase in the accuracy of the proposed method in long-term demand forecasting in the electricity supply chain of Espidan ironstone industries. Manuscript profile -
Open Access Article
359 - The Electricity Consumption Prediction using Hybrid Red Kite Optimization Algorithm with Multi-Layer Perceptron Neural Network
Jalal Raeisi-Gahruei Zahra BeheshtiSince the electricity consumption’s prediction is one of the most important aspects of energy manage­ment in each country, various methods based on artificial intelligence have been proposed to manage it. One of these methods is Artificial Neural Networks (ANN MoreSince the electricity consumption’s prediction is one of the most important aspects of energy manage­ment in each country, various methods based on artificial intelligence have been proposed to manage it. One of these methods is Artificial Neural Networks (ANN). To improve the performance of ANNs, an efficient algorithm is necessary to train it. Back Propagation (BP) algorithm is the most common algorithm employed in training ANNs, which is based on gradient descent. Since BP may fall in local optima, it cannot provide a good solution in some problems. To overcome this shortcoming, optimiz­ation algorithms like meta-heuristic algorithms can be applied to train ANNs. In this study, a new meta-heuristic algorithm called Red Kite Optimization Algorithm (ROA) is introduced, which is inspired by the social life of red kites in nature. The ROA has several advantages such as simplicity in structure and implementation, having few parameters and good convergence rate. The perfprmance of ROA is compared with some recent metaheuristic algorithms on benchmark functions of CEC2018. Also, it is employed to train Multi-Layer Perceptron (MLP) for the electricity consumption prediction at peak load times in Iran. The results show the good performance of proposed algorithm compared with competitor algorithms in terms of solution accuracy and convergence speed. Manuscript profile -
Open Access Article
360 - Coping With the Loss of Quality of Job Future Predictors in Grid Computing Environments
Reza Ghaemi hosein salami Mehrdad JalaliDistributed processing environments, such as grids, are one of the most important platforms for meeting the user's processing needs. These environments have the potential to meet the needs of users, but they also have their own problems, including the failure of the job MoreDistributed processing environments, such as grids, are one of the most important platforms for meeting the user's processing needs. These environments have the potential to meet the needs of users, but they also have their own problems, including the failure of the jobs. Several attempts have been made to overcome this problem, which in general can be divided into two categories of resource side methods and job side methods. All these methods need some kind of prediction of the resources or jobs status in order to pursue a proactive approach to failures. However, due to the dynamics of these environments, the developed models quickly lose their quality and thus can not effectively help with the methods mentioned. In this paper, first, by identifying the reasons for reducing the quality of predictors in the grid environment, a solution has been proposed to deal with it, and then the proposed solution has been applied in the context of job failures. The results of experiments on the two experimental environments of AuverGrid and Grid5000 showed that the proposed method would increase the quality by 0.02 and 0.06 respectively in these two environments. Manuscript profile -
Open Access Article
361 - Prediction of Success in Neurofeedback Treatment for Attention-Deficit Hyperactivity Disorder before Starting Treatment
Nikoo Khanahmadi MR YousefiIn this paper, the method of predicting the treatability of patients suffering from hyperactivity with neurofeedback training with the help of extracting the frequency band of the electroencephalogram (EEG) signal and using the brain-functional communication evaluation MoreIn this paper, the method of predicting the treatability of patients suffering from hyperactivity with neurofeedback training with the help of extracting the frequency band of the electroencephalogram (EEG) signal and using the brain-functional communication evaluation criterion is done to determine the person's treatability before starting the neurofeedback treatment. This algorithm consists of six steps: In the first step, a data set of EEG signal recording during neurofeedback stimulation from 60 students in the age group of 7 to 14 years (regardless of gender) with hyperactivity in two treatable and non-treatable classes was obtained from the Mendelian database. In the second step, primary filtering has been done to reduce the noise of the data set using a pre-processing block. In the third step, the frequency distribution of the alpha and beta bands is extracted from the noise reduction signals. In this type of data, the difference in the EEG components of each group can be expressed by measuring brain-functional communication and using the phase lock index (PLI), which is used to detect the existence of a connection between the brain lobes involved once using the probability value index. In the t-test statistical test and to increase the accu­ra­c­y, the genetic algorithm was used to identify the effective electrodes in the treatment. So, the fourth step is to extract the feature, which is to measure the amount of brain communication in the brain signal recording electrodes. In the fifth step, it is to reduce the feature space, the results show show that the lobes involved during neurofeedback stimulation are the frontal and central lobes, and among the 32 EEG recording channels, only the data of 6 channels C3, FZ, F4, CZ, C4, and F3 show a significant difference in the amount of brain communication during stimulation. and finally, in the sixth step, by using different classifications, the output of the combination of classifications was the label of one of two classes, treatable or non-treatable. In this proposed method, the correctness cri­te­rion is used to express the research result, and finally the percentage of correctness obtained is 90.6%. Manuscript profile -
Open Access Article
362 - Static Voltage Stability Analysis by Using SVM and Neural Network
Mehdi Hajian Asghar Akbari Foroud Hossein NorouzianVoltage stability is an important problem in power system networks. In this paper, in terms of static voltage stability, and application of Neural Networks (NN) and Supported Vector Machine (SVM) for estimating of voltage stability margin (VSM) and predicting of voltage MoreVoltage stability is an important problem in power system networks. In this paper, in terms of static voltage stability, and application of Neural Networks (NN) and Supported Vector Machine (SVM) for estimating of voltage stability margin (VSM) and predicting of voltage collapse has been investigated. This paper considers voltage stability in power system in two parts. The first part calculates static voltage stability margin by Radial Basis Function Neural Network (RBFNN). The advantage of the used method is high accuracy in online detecting the VSM. Whereas the second one, voltage collapse analysis of power system is performed by Probabilistic Neural Network (PNN) and SVM. The obtained results in this paper indicate, that time and number of training samples of SVM, are less than NN. In this paper, a new model of training samples for detection system, using the normal distribution load curve at each load feeder, has been used. Voltage stability analysis is estimated by well-know L and VSM indexes. To demonstrate the validity of the proposed methods, IEEE 14 bus grid and the actual network of Yazd Province are used. Manuscript profile -
Open Access Article
363 - Short-Term Load Forecasting of Distribution Power System for Weekdays Using Old Data
Bahador Fani Soleyman Fehresti Sani Ehsan AdibEstimation of daily load in distribution companies which is performed to present the results to the DMS, is necessary. Daily load forecasting of power systems has traditionally been considered. Because load patterns are influenced by several factors such as climate, eco MoreEstimation of daily load in distribution companies which is performed to present the results to the DMS, is necessary. Daily load forecasting of power systems has traditionally been considered. Because load patterns are influenced by several factors such as climate, economy and society, it is difficult to predict the load exactly. That's why in recent years the use of intelligent algorithms to predict it, is growing. In this project, the short-term load forecasting is performed in a hybrid approach. Due to the different behavior in different days, various methods have been used to predict the load. With studying different methods of load prediction, finally, finally exponential smoothing algorithm was used to predict the exact load in the weekdays. Manuscript profile -
Open Access Article
364 - New Prognostic Index to Detect the Severity of Asthma Automatically Using Signal Processing Techniques of Capnogram
Mohsen Kazemi Aik Howe TeoIn this paper, a new prognostic index to detect the severity of asthma by processing capnogram signals is presented. Previous studies have shown significant correlation between the capnogram and asthmatic patient. However, most of them used conventional time-domain meth MoreIn this paper, a new prognostic index to detect the severity of asthma by processing capnogram signals is presented. Previous studies have shown significant correlation between the capnogram and asthmatic patient. However, most of them used conventional time-domain methods and based on assumption that the capnogram is a stationary signal. In this study, by using linear predictive coding (LPC) coefficients and autoregressive (AR) modelling (Burg method), the capnogram signals are processed. Then, a number of six features including α1, and α4 from LPC and power spectral density (PSD) parameters through AR modelling are extracted. After that, by means of receiver operating characteristic (ROC) curve, the effectiveness of the extracted features to differentiate between asthmatic and nonasthmatic conditions is justified. Finally, selected features are used in a Gaussian radial basis function (GRBF) network. The output of this network is an integer prognostic index ranging from 1 to 10 (depends on the severity of asthma) with an average good detection rate of 90.15% and an error rate of 9.85%. In the other word, based on the results, sensitivity and specificity of this algorithm are 93.54% and 98.29%, respectively. This developed algorithm is purposed to provide a fast and low-cost diagnostic system to help healthcare professional involved in respiratory care as it would be possible to monitor severity of asthma automatically and instantaneously. Manuscript profile -
Open Access Article
365 - Fast Intra and Inter Prediction Mode Decision of H.264/AVC for Medical Image Compression Based on Region of Interest
Mehdi Jafari Homayoun Mahdavi-Nasab Shohreh KasaeiThis paper aims at applying H.264 in medical video compression applications and improving the H.264 Compression performance with better perceptual quality and low coding complexity. In order to achieve higher compression of medical video, while maintaining high image qu MoreThis paper aims at applying H.264 in medical video compression applications and improving the H.264 Compression performance with better perceptual quality and low coding complexity. In order to achieve higher compression of medical video, while maintaining high image quality in the region of interest, with low coding complexity, here we propose a new model using H.264/AVC that uses lossless compression in the region of interest, and very high rate, lossy compression in other regions. This paper proposes a new method to achieve fast intra and inter prediction mode decision that is based on coarse macroblocks for intra and inter prediction mode decision of the background region and finer macroblocks for region of interest. Also the macroblocks of the background region are encoded with the maximum quantization parameter allowed by H.264/AVC in order to maximize the number of null coefficients. Experimental results show that the proposed algorithm achieves a higher compression rate on medical videos with a higher quality of region of interest with low coding complexity when compared to our previous algorithm and other standard algorithms reported in the literature. Manuscript profile -
Open Access Article
366 - Developing a model for predicting student performance on centralized test Based on Data Mining
mostafa yousefi Tezerjan Esrafil Ala Maryam MollabagherThe aim of this study is to provide a model for predicting University of Applied Science & Technology students' scores in centralized exams in the coming semesters of the university. For this purpose, the status of the 19/207 student/ course grades has been studied MoreThe aim of this study is to provide a model for predicting University of Applied Science & Technology students' scores in centralized exams in the coming semesters of the university. For this purpose, the status of the 19/207 student/ course grades has been studied in 8 courses in 6 provinces and 28 educational centers, that have been held in an associate's and bachelor's degree level and concurrently across the country in the second semester of 1397-98 And by using the feature selection method, the most effective ones were selected. To clarify the relationships between the selected features and the decision tree model with C5.0 algorithm using SPSS Modeler software, with 10 effective indicators, a model for predicting students' scores in the next semester is presented in the courses approved for the centralized exam. This predictive model can be effective in making the learning process more efficient in the academic system. The results of these models include suggestions for modifying the test process, finding students and centers, and out-of-pattern conditions for further monitoring and identifying centers whose students' average GPAs were high but poor on the centralized test. Manuscript profile -
Open Access Article
367 - شناسایی دسته های پیش بینی همپوشان : تمرکز بر کتب درسی زبان انگلیسی با اهداف ویژه
فرحناز بهلولی اسگوییمفهوم "پیش بینی" به عنوان یک ابزار بلاغی آینده نگر در بهبود توانایی های خواندن زبان آموزان در حوزه زبان انگلیسی با اهداف ویژه بر پایه این فرض اهمیت ویژه میابد که وقتی ساختار بلاغی متن توسط زبان آموز درک شود، وی می تواند از آن برای پیش بینی نوع اطلاعات پیش رو بهره ببرد. Moreمفهوم "پیش بینی" به عنوان یک ابزار بلاغی آینده نگر در بهبود توانایی های خواندن زبان آموزان در حوزه زبان انگلیسی با اهداف ویژه بر پایه این فرض اهمیت ویژه میابد که وقتی ساختار بلاغی متن توسط زبان آموز درک شود، وی می تواند از آن برای پیش بینی نوع اطلاعات پیش رو بهره ببرد. هدف این مطالعه بررسی امکان مرتبط کردن سیگنالهای متنی " مقوله های پیش بینی" با دانش محتوای متن بود. برای این منظور، یک پژوهش توصیفی کیفی بر روی داده ها مشتمل بر 10 فصل از 5 کتاب درسی در رشته مهندسی عمران با استفاده ازمدل تحلیلی طراحی شده توسط "تادرس" بر پایه مفهوم پیش بینی اتخاذ شد. شش دسته"مقوله پیشبینی" معرفیشده توسط تادروس که زیربنای این مدل هستند، شامل شمارش، برچسبگذاری پیشرفته، گزارش، بازپیدایی، فرضیه سازی و سؤال ، بهطور مداوم در متون انتخاب شده بررسی شدند. یافتههای این مطالعه یک دسته پیشبینیکننده جدیدی به نام «مقولههای پیشبینیهمپوشان» را نشان داد که در آن دو یا سه دسته مقوله های پیشبینی، دقیقاً روی یکدیگر همپوشانی دارند.بر مبنای نتایج بدست آمده از این مطالعه ، آگاه سازی زبان آموزان ، معلمان و طراحان کتب آموزشی در مورد وجود چنین مقوله های پیش بینی میتواند مزایای قابل توجهی برای همه اعضای جامعه زبان انگلیسی با اهداف ویژه به همراه داشته باشد. Manuscript profile -
Open Access Article
368 - تحلیل توزیع فضایی جمعیت استان زنجان طی سالهای 90-1365 و پیش بینی جمعیت تا سال 1404
محسن کلانتری کیومرث یزدان پناه سمیه نوری -
Open Access Article
369 - آﺷﮑﺎرﺳﺎزی ﺗﻐﯿﯿﺮات ﮐﺎرﺑﺮی و ﭘﻮﺷﺶ اراﺿﯽ در اﻓﻖ 2025 ﺑﺎ اﺳﺘﻔﺎده از ﻣﺪل اتوماتای سلولی CA (ﻣﻄﺎﻟﻌﻪ ﻣﻮردی: شمال شهر اصفهان)
اعظم خدادادی رحیم سرور مجید ولی شریعت پناهی -
Open Access Article
370 - پیش بینی رویدادهای هواشناسی با استفاده از مدل خاکستری بهبود یافته (مطالعه موردی: ایستگاه هوا شناسی استان قزوین)
مریم کریمی خواجه قیاسی علیرضا علینژاد نظریه سیستم خاکستری زمانی استفاده می شود که اطلاعات کافی از جامعه مورد مطالعه در دست نیست. مدل پیش بینی خاکستری مناسب زمانی می باشد که تنوع اطلاعات ثابت و مشخص است. مدل خاکستری می تواند برخی از محاسبات اضافی برای بهبود فعالیت های پیش بینی زمانی که داده ها کافی نیس More نظریه سیستم خاکستری زمانی استفاده می شود که اطلاعات کافی از جامعه مورد مطالعه در دست نیست. مدل پیش بینی خاکستری مناسب زمانی می باشد که تنوع اطلاعات ثابت و مشخص است. مدل خاکستری می تواند برخی از محاسبات اضافی برای بهبود فعالیت های پیش بینی زمانی که داده ها کافی نیستند به کار رود. با استفاده از مدل خاکستری بهبود یافته، خطای ارزیابی به طور قابل توجهی کاهش می یابد. این مطالعه با استفاده از میانگین حداکثر داده های دمای روزانه جمع آوری شده توسط ایستگاه هواشناسی قزوین از آگوست 2001 تا اوت 2013 انجام شد. یافته ها نشان داد که روش متابولیسم مدل خاکستری می تواند اشتباهات را کاهش داده و دقت پیش بینی میانگین متغیر حداکثر دمای روزانه را بهبود بخشد. Manuscript profile -
Open Access Article
371 - .
Tahmineh Shojaatzadeh Narges Oskooei -
Open Access Article
372 - پیشبینی نواحی اپیتوپی سلولهایB و T آنتیژن حفاظتی در باکتری Bacillus anthracis
م. طهمورثپور ن. نظیفی ز. پیرخضرانیانآنتیژن حفاظتی (PA) زیر واحدی از توکسین سیاه زخم در باکتری Anthracis میباشد که به عنوان یک عامل مهم در واکسنهای حفاظت در برابر بیماری سیاه زخم شناخته شده است. یکی از اهداف طراحی واکسنهای نوترکیب اجتناب از عوارض جانبی ارگانیسمهای کشته شده یا ضعیف شده با استفاده از اپ Moreآنتیژن حفاظتی (PA) زیر واحدی از توکسین سیاه زخم در باکتری Anthracis میباشد که به عنوان یک عامل مهم در واکسنهای حفاظت در برابر بیماری سیاه زخم شناخته شده است. یکی از اهداف طراحی واکسنهای نوترکیب اجتناب از عوارض جانبی ارگانیسمهای کشته شده یا ضعیف شده با استفاده از اپیتوپهای خطی خنثیساز آنتیژنهای حفاظتی میباشد. مطالعه حاضر با هدف تعیین اپیتوپهای غالب بر اساس آنالیزهای چند پارامتری انجام شد. از سرورهای بیوانفورماتیکی آنلاین شناخته شده به منظور پیشبینی اپیتوپها استفاده شد و بر اساس بالاترین امتیاز و بیشترین تکرار در نرم افزارهای مورد استفاده، بهترین اپیتوپها انتخاب شدند. تجزیه و تحلیلهای بیشتر در مورد اپیتوپهای پیشبینی شده با استفاده از نرم افزار آنلاین VaxiJen 2.0 و سرورهای هضم پروتئینی (Protein Digest) انجام پذیرفت. در میان اپیتوپهای انتخاب شده در مراحل قبل، آنهایی که دارای بالاترین آنتیژنسیته با حد آستانه 5/0 و کمترین جایگاه محدودکننده پروتئازهای دستگاه گوارش بودند به عنوان اپیتوپهای نهایی انتخاب شدند. اپیتوپهای نهایی برای سلولهای B شامل اسیدآمینههای 308-292، 521-507 و 719-706 بودند. همچنین اسیدآمینههای 31-17، 329-315 و 400-385 به عنوان بهترین اپیتوپهای کلاس MCHI سلولهای T و اسیدآمینههای شماره 464-455 و 669-661 به عنوان بهترین اپیتوپهای انتخابی برای کلاس MCHII در سلولهای T پیشبینی شدند. از آنجایی که وجود ساختار پیچههای تصادفی موجب بالا رفتن احتمال شکلگیری اپیتوپ آنتیژنتیک در ساختار پروتئین میشود، آنالیز نهایی ساختار دوم برای اپیتوپهای نهایی PA نشان داد که تمام این اپیتوپها دارای ۱۰۰ درصد ساختار مارپیچ تصادفی (نامنظم) هستند. Manuscript profile -
Open Access Article
373 - پاسخ انتخاب برای وزن بدن در بلدرچین ژاپنی (Coturnix coturnix japonica
اس. هوسن آ.م. عبد الرحمان ال-خدری آ.م. حسنمطالعه حاضر به بررسی اثر انتخاب برای وزن بدن (BW) بر عملکرد تولیدی، BW پیش­بینی شده و بهبود ژنتیکی مرتبط با صفات در بلدرچین ژاپنی است. جمعیت پایه، والدین منتخب و فرزندان F1 مورد آزمون قرار گرفتند. پرورش در قفس و لانه صورت گرفت. از تعداد کل 240 پرنده در دو نسل متوالی Moreمطالعه حاضر به بررسی اثر انتخاب برای وزن بدن (BW) بر عملکرد تولیدی، BW پیش­بینی شده و بهبود ژنتیکی مرتبط با صفات در بلدرچین ژاپنی است. جمعیت پایه، والدین منتخب و فرزندان F1 مورد آزمون قرار گرفتند. پرورش در قفس و لانه صورت گرفت. از تعداد کل 240 پرنده در دو نسل متوالی، 27 نر و 54 ماده (به عنوان والدین منتخب) به کار گرفته شدند. وزن بدن از معادله رگرسیون چندگانه، آنالیز کوواریانس و مدل­های مرکب برآورد گردیده و پاسخ انتخاب، وراثت­پذیری تحقق یافته و همبستگی ژنتیکی برای BW، افزایش وزن (WG)، مصرف خوراک (FI) و ضریب تبدیل خوراک (FCR) محاسبه شدند. نتایج نشان داد که پاسخ انتخاب برای BW، WG، FI و FCR به ترتیب برابر با 48/11 گرم، 04/27 گرم، 37 گرم و 2/0- بود. وراثت­پذیری­های برآورد شده برای صفات فوق نیز به ترتیب برابر با 78/0، 67/0، 52/0 و 77/0 بود. معادله پیش­بینی شده (معادله DUHOK) برای BW به عنوان متغیر وابسته به وزن بدن اولیه و نسبت جنس نیز به دست آورده شد. پاسخ نهایی برای وزن بدن به صورت 84/5 درصد BW زنده تعیین گردید. Manuscript profile -
Open Access Article
374 - پیشبینی اپی توپهای سلولهایB و Tآنتیژن Omp25 از باکتری بروسلا ملی تنسیس به منظور طراحی واکسن نوترکیب گوسفندی
س. یوسفی م. طهمورثپور م.ه. سخاوتیبروسلوز یکی از رایج ترین بیماریهای دامی است که توسط باکتری گرم منفی بروسلا ایجاد می­شود. با توجه به ضرر­های جدی اقتصادی و درمانی این بیماری که برای دام و انسان همواره به ارمغان دارد تلاش­های بسیاری جهت جلوگیری و درمان این بیماری توسط واکسن­های نوترکیب ب Moreبروسلوز یکی از رایج ترین بیماریهای دامی است که توسط باکتری گرم منفی بروسلا ایجاد می­شود. با توجه به ضرر­های جدی اقتصادی و درمانی این بیماری که برای دام و انسان همواره به ارمغان دارد تلاش­های بسیاری جهت جلوگیری و درمان این بیماری توسط واکسن­های نوترکیب بر پایه آنتیژن­های غشای پروتئینی خارجی صورت می­گیرد. بدین منظور هدف از مطالعه حاضر بررسی خصوصیات بیوانفورماتیکی آنتی ژن Omp25 به عنوان یکی از آنتیژنهای غالب غشای پروتئینی باکتری بروسلا بوده است. در این پژوهش از نرم افزار­های بیوانفورماتیکی مختلفی برای پیشبینی اپی توپ­های B وT، ساختار دوم و سوم پروتئین، خصوصیات ایمنیزایی و ویژگی­های هضم پروتئین استفاده گردید. پیش از استفاده از نرم افزارها میزان دقت آنها توسط دادههای تجربی اعتبار سنجی گردید. نتایج آنالیز بیوانفورماتیکی نشان داد که پنج اپی توپ برای سلولهای B در موقعیتهای 44-26، 79-59، 112-88، 166-146، 202-175 و پنج اپی توپ برای سلولهای T در مکانهای 10-1، 22-14، 132-122، 162-154 و 213-206 وجود دارد. تمامی اپی توپهای شناسایی شده به جز اپی توپهای 10-1 و 22-14 دارای توانایی ایمنیزایی بودند. نهایتاً اپی توپ ناحیه 162-154 به عنوان یک اپی توپ مشترک بین سلولهای B و T جهت طراحی واکسن نوترکیب پیشبینی گردید. Manuscript profile -
Open Access Article
375 - برآورد وزن بدن بر مبنای ابعاد قلب گوسفندان ساردی و تیماهدیت با استفاده از مدلهای مختلف
آی. بوجنانه اس. هلهالیهدف از این مطالعه تعیین رابطه بین وزن بدن (BW) و ابعاد قلب (HG) در گوسفندان ساردی و تیماهدیت و برازش یک معادله پیش­بینی BW بر مبنای HG بوده است. داده­های مورد استفاده در این مطالعه شامل 476 رکورد BW و HG (227 رکورد در ساردی و 249 رکورد در تیماهدیت) بود که از نره Moreهدف از این مطالعه تعیین رابطه بین وزن بدن (BW) و ابعاد قلب (HG) در گوسفندان ساردی و تیماهدیت و برازش یک معادله پیش­بینی BW بر مبنای HG بوده است. داده­های مورد استفاده در این مطالعه شامل 476 رکورد BW و HG (227 رکورد در ساردی و 249 رکورد در تیماهدیت) بود که از نرها و ماده­ها در سنین مختلف و از 33 مزرعه خصوصی جمعآوری گردیدند. میانگین BW و HG در ساردی به ترتیب 2/12 ± 8/34 کیلوگرم و 3/16 ± 0/74 سانتی­متر و در تیماهدیت به ترتیب 7/22 ± 2/39 کیلوگرم و 4/16 ± 4/78 سانتی­متر در تیماهدیت بود. ضرایب همبستگی بین BW و HG که به ترتیب در ساردی و تیماهدیت برابر با 958/0 و 944/0 بوده، نشان ­دهنده وجود همبستگی بالا بین این دو متغیر است. شش مدل پیش­بینی شامل رگرسیون خطی ساده، رگرسیون­های درجه سه و چهار چند جمله­ای و سه رگرسیون غیر خطی (گومپتز، آلومتریک و میشرلیک) برای این داده­ها برازش یافتند. این مدل­ها برای کل داده­ها (صرفنظر از نژاد و جنس)، به طور جداگانه برای همه حیوانات یک نژاد صرفنظر از جنس (مختص نژاد) و به طور جداگانه برای نرها و ماده­ها صرفنظر از نژاد (مختص جنس) به کار گرفته شدند. برای تعیین بهترین مدل رگرسیونی برازش یافته، ضریب تعین (2R یا شبه 2R) میانگین مربعات باقیمانده (MSE) و معیار اطلاعات آکایک (AIC) مورد استفاده قرار گرفتند. هر شش مدل به خوبی با مجموعه داده­ها انطباق داشتند. زیرا 2R یا شبه 2R آنها از 892/0 تا 969/0 متغیر بوده است. با این حال براساس سایر معیارهای انتخاب، چنین به نظر می­رسد که مدل درجه سوم چند جمله­ای بهترین مدل بوده و مدل آلومتریک بایستی نادیده گرفته شود. مشاهدات دور در هر سه مدل برتر با کمک باقیمانده­های استودنت و مقادیر مطلق بزرگتر از دو انحراف معیار که نشان دهنده انحراف معنی ­دار بوده است، کنترل گردیدند. سپس مشاهدات پرت حذف گردیده و بهترین مدل­ها بر روی مجموعه­ داده­های پاکسازی شده پیاده گردیده و مقایسه شدند. بدین ترتیب، برای کل داده­ها، نژاد ساردی و ماده­ها، مدل میشرلیک مناسب بوده و برای نژاد تیماهدیت و نرها، به ترتیب مدل­های درجه سوم و گومپتز مناسب بوده­اند. بنابراین یک معیار جهت کمک به پرورش دهندگان در مدیریت بهتر گوسفندان در هر دسته ارائه گردید. Manuscript profile -
Open Access Article
376 - قابلیت پیشبینی مدلهای آماری پیشبینی ژنومی هنگامیکه صفت مورد بررسی تحت تأثیر معماری کاملاً افزایشی است
م. مومن ا. آیتآللهی مهرجردی ا. شیخی ع. اسماعیلیزاده م. اسدی فوزییک مطالعه شبیه سازی شده به منظور بررسی قابلیت پیش­بینی روش­های پارامتری و ناپارامتری پیش­بینی ژنومی، هنگامی که صفت کمی تحت تأثیر معماری ژنتیکی کاملا افزایشی صورت گرفت. بدین منظور یک صفت کمّی با وراثت­پذیری کاملاً افزایشی (h2=0.3)، تحت تأثیر 300 جایگاه کن Moreیک مطالعه شبیه سازی شده به منظور بررسی قابلیت پیش­بینی روش­های پارامتری و ناپارامتری پیش­بینی ژنومی، هنگامی که صفت کمی تحت تأثیر معماری ژنتیکی کاملا افزایشی صورت گرفت. بدین منظور یک صفت کمّی با وراثت­پذیری کاملاً افزایشی (h2=0.3)، تحت تأثیر 300 جایگاه کنترل کننده صفت کمّی (QTL)، شبیه­سازی شد. قابلیت پیش­بینی 14 مدل آماری براساس چهار معیار اریبی، مجموع مربعات خطا، همبستگی بین مقدار فنوتیپ مشاهده شده و ارزش اصلاحی ژنومی برآورد شده وهمچنین، همبستگی ارزش اصلاحی برآورد شده و ارزش اصلاحی واقعی برآورد گردید. نتایچ نشان داد که مدل­های پیش­بینی ژنومی پارامتری قابلیت پیش­بینی بهتری نسبت به مدل­های غیرپارامتری دارند. همچنین، تمامی مدل­های پارامتری به غیر از روش RR-BLUP بیشتر واریانس فنوتیپی را می­توانند توجیه کنند و مجموع مربعات خطای کمتر، همبستگی پیش­بینی و همبستگی ارزش اصلاحی برآورد شده و ارزش اصلاحی واقعی بالاتری برآورد گردید. همچنین این روش­ها کمترین اریبی را نشان دادند و مقادیر پیش­بینی شده حاصل از آنها نااریب­تر بود. روش ناپارامتری Random forest بدترین عملکرد را نشان داد. به طور کلی نتایج این شبیه­سازی نشان داد که، تفاوت بسیار زیادی بین روش­های ناپارامتری هنگامیکه صفت تحت تأثیر معماری ژنتیکی غیر افزایشی می­باشد وجود دارد. این اتفاق ممکن است زمانیکه اثرات غلبه و اپیستاتیک به عنوان واریانس غیر افزایشی در معماری ژنتکی صفت دخیل باشند وجود نداشته باشد. Manuscript profile -
Open Access Article
377 - Feasibility Study of Using Photovoltaic Systems in Water and Wastewater Industry (Case Study: Tehran Water and Wastewater Company)
Ensieh Ozgoli Younes Noorollahi Reza Arjmandi Ali MohammadiSince water and wastewater companies are one of the significant energy consumers in urban industries, there is a substantial share to increase electricity demand and as a result, increasing the power plants load. The purpose of this study is to present a new evaluation MoreSince water and wastewater companies are one of the significant energy consumers in urban industries, there is a substantial share to increase electricity demand and as a result, increasing the power plants load. The purpose of this study is to present a new evaluation approach for using solar energy in the water and wastewater industry. Therefore, while consideration of the energy consumption in the six regions of Tehran Water and Wastewater Company, requirements for the installation and operation of photovoltaic systems in this company has been investigated. In the present study, the objective functions are energy consumption costs and greenhouse gas emissions; Also, solar energy potential, increasing population rate and water consumption are the most important independent variables and forecasted electricity consumption, carbon tax, and electricity sales price are also dependent variables. The results of this study, which can be based on using the regression model, show that the increase in electricity consumption and costs are 1.5 and 3 times in this period, respectively. To calculate the amount of greenhouse gas emissions, the three scenarios are implemented and compared with the replacement of 5, 20, and 30% of the company required electricity by photovoltaic systems. The reduction in CO2 emissions due to the production of 30% of electricity consumption with solar energy, amounted to 26,712 thousand tons. On the other hand, taxing more than $ 10 per ton of CO2 emissions changes the consumption pattern and reduces the cost of electricity consumption in this industry by $ 5,987,086. Manuscript profile -
Open Access Article
378 - Measuring the incremental coefficient of water and sewage effluent and its applications in predicting the rotational economy of water for intermediate consumption and final demand based on the input-output table model
kourosh javadi pashakiFrom demand perspective, water is an essential and irreplaceable commodity in the household basket and production intermediate demand in the economic sectors. In economics, the price of a commodity depends on the final demand for it but this issue is not the same for wa MoreFrom demand perspective, water is an essential and irreplaceable commodity in the household basket and production intermediate demand in the economic sectors. In economics, the price of a commodity depends on the final demand for it but this issue is not the same for water due to its low price. All the economic sectors are dependent on water and no sector can operate and offer services without it. Water is in close contact with environment. The economy based on recirculating of water and use of sewage effluent in the manufacturing sector leads to decrease in usage of underground water. This paper uses the statistics of water accounting and based on the input-output tables, calculates the incremental coefficient of sewage effluent, surface water, underground water, Water abstraction from the sea, and usage of water in industrial units in different sectors of economy and predicts the amount of water consumption based on the national economic growth and population growth for the year 1410. Manuscript profile -
Open Access Article
379 - Forecasting the discharge of the Zayandeh Rood River at the Ghleeh Shahrokh station using deep learning techniques
Mohammad MehraniAbstract- Water discharge is a term in the water industry that refers to the amount of water that passes through a certain point per unit of time. Discharge rate is the amount of water that passes through a specific point such as a river,, water channel, dam valve, pipe MoreAbstract- Water discharge is a term in the water industry that refers to the amount of water that passes through a certain point per unit of time. Discharge rate is the amount of water that passes through a specific point such as a river,, water channel, dam valve, pipe or any other structure such as a faucet cartridge in a unit of time. In the metric system, water discharge rate is expressed in terms of cubic meters per second, cubic meters per hour, or liters per second. The unit of cubic meters per second is used for large flows such as rivers and large canals, and the unit of liters per second is used for the flow of water in wells and water that enters leaks. Measuring the discharge of the river has many effects on people's lives. Knowing the amount of water entering the areas of a river's catchment area is very important in agriculture, potential risks to human and animal life, industries, etc. Therefore, predicting river discharge can lead to effective management and prevent serious damage in the mentioned areas. According to the mentioned cases, the purpose of the presented paper is to predict the river discharge using deep learning techniques. In order to do this, the discharge of the Zayandeh Rood River at Qala Shahrokh station has been investigated and predicted using two techniques - ANFIS and LSTM. The simulation results show 93% to 94% accuracy in predicting the discharge of the studied river. Manuscript profile -
Open Access Article
380 - Examining the effects of supervisor rudeness on job entanglement and organizational cynicism with the mediating role of employees' self-efficacy
Majid Maharani Barzani Mehrdad Sadeghi Ali Rashidpour.The aim of the present study is to determine the effects of supervisor rudeness on job entanglement and organizational cynicism with the mediating role of employees' self-efficacy. The statistical population of this study was all the employees of Chaharmahal and Bakhti More.The aim of the present study is to determine the effects of supervisor rudeness on job entanglement and organizational cynicism with the mediating role of employees' self-efficacy. The statistical population of this study was all the employees of Chaharmahal and Bakhtiari universities, whose number is 2255, according to the size of each The sample size of 660 people was selected using the Cochran formula, and the sample people were selected using the stratified sampling method according to the size of each stratum. To collect the required data in this research, standard questionnaires were used and their validity and reliability were tested, and they were highly valid and reliable. The results of the analysis conducted in the research showed that supervisor politeness through employees' self-efficacy has a positive and significant effect on job entanglement, and the coefficient of this effect is 0.11, and supervisor rudeness through employees' self-efficacy has a positive and significant effect on organizational pessimism. It has a positive and significant effect, and the coefficient of this effect is 0.22, and the direct effect of the supervisor's impoliteness on job entanglement is also significant and positive. The coefficient of this effect is 0.12 and also the direct effect of supervisor's impoliteness on organizational pessimism is significant and positive. The coefficient of this effect is 0.52 Manuscript profile -
Open Access Article
381 - رابطه خطای پیش بینی سود و جابجایی مدیرعامل در شرکتها
فرزین رضایی طاهره رضی کاظمی -
Open Access Article
382 - Predicting product choice by customers based on neuromarketing with Chaotic salp swarm algorithm
Marzieh Maleki Zahra Dasht LaliUnderstanding how consumers make decisions is one of the important things in customer behavior that is addressed by neuromarketing. The purpose of this article is to present a new solution in neuromarketing by receiving brain signals and extracting and selecting importa MoreUnderstanding how consumers make decisions is one of the important things in customer behavior that is addressed by neuromarketing. The purpose of this article is to present a new solution in neuromarketing by receiving brain signals and extracting and selecting important features and classification to increase the prediction of product selection by customers. In this article, brain signals from twenty-five participants who have seen the products have been received and characterized by the high-order spectrum method. In order to select the best features, in this article, the swarm algorithm of salp chaos has been presented, which can identify the effective features with high search power, and for the final prediction, different classifications have been used in the form of multiple learning. In the proposed model, the high-order spectra method was applied in extracting the phase information of the electroencephalogram signal in order to investigate the relationship between liking and disliking the product, which included more than seven hundred features. Then feature selection was used with the improved Salp swarm algorithm with logistic chaos mapping and the features were reduced from 742 to 198 features. The results showed that the proposed model was able to have an average accuracy of 75.99% in detecting the choice of users in all products, which shows a 3.75% improvement in the results compared to similar researches. Manuscript profile -
Open Access Article
383 - بررسی تاثیر هموار سازی سود بر قدرت پیش بینی کنندگی سود هر سهم در شرکت های تولیدی پذیرفته شده در بورس اوراق بهادار تهران
بیژن عابدینی افشین آرمین اعظم سلمانی پور کرانی -
Open Access Article
384 - The advice of stories based on prediction in literary texts
timoor MalmirAccording to holy Koran only Allah is aware of future and making prediction by prophet or Imams is possible under the will of Allah. Therefore, it is necessary to make clear what the goal of making prediction is in the literary texts within the framework of MoreAccording to holy Koran only Allah is aware of future and making prediction by prophet or Imams is possible under the will of Allah. Therefore, it is necessary to make clear what the goal of making prediction is in the literary texts within the framework of expressing dreams by astronomers, fortune-tellers ?the main goal of predictions are that everything that human do is the result of his/her action. To narrate a story that show the ability of a person of knowing about future is an advice for human that his knowledge is not related to him/her because it doesn’t make ability. In some cases, making prediction is a way by which wise men give advice to the oppressors. Sometime the claim of making prediction is a way for practicing hidden plans. Manuscript profile -
Open Access Article
385 - The Role Of Flood Anticipation And Warming Systems In Reducing Flood Adverse Impacts
Hossain Mohammadi Mehran Maghsoudi Gholam Reza RowshanIn this field, flood one of the most dangers disasters for people of many countries face it and is one of the most destroying disasters among 15 known natural climatology all over the world. For example, about 196 million people in over 90 countries are exposed to dange MoreIn this field, flood one of the most dangers disasters for people of many countries face it and is one of the most destroying disasters among 15 known natural climatology all over the world. For example, about 196 million people in over 90 countries are exposed to danger of flood water.The increase in the population and the shortage of agricultural lands led to human population movement to the flood water plains and this intensifies the danger of flood water and its effects. But nowadays, considering the destroying effects of flood water on the human societies, structural methods of protection against flood water such as flood water bands and other methods of controlling and directing flood water, can be efficient only when the design capacity of these structures is high. But when these structures break, always a remaining risk exists. In most cases, such structures may be improper or their execution may be impossible because of environmental reasons and therefore non-structural methods are needed. The flood water warning for directing of the remaining risk is necessary and it is one of the most efficient methods of non-structural methods for flood water management. Manuscript profile -
Open Access Article
386 - Study the Qualitative and Quantitative Indicators and Estimating Needed Home in Rasht City until 1400
ایرج غمخوار علیرضا کشوردوست رضا حسن پور پری موسی پور میاندهیMost cities of (our) country have been changed due to population increase in recent decades, and this reason has increased the importance of paying attention to urban and home planning. Thus home standard indicators are among the most key and important tools in home pla MoreMost cities of (our) country have been changed due to population increase in recent decades, and this reason has increased the importance of paying attention to urban and home planning. Thus home standard indicators are among the most key and important tools in home planning and with their study it is possible to define the effective parameters in home field and facilitating its planning and decision making. Quantitative indicators are family density, number of homes, family growth rate, density index of person per home, room average per home, room average per each family, individual average per each room. Research Qualitative indicators are as follows: forms of home occupation, types of building materials, facilities, equipment and quality of homes. Home situation is determined by studying the qualitative and quantitative indicators of home in Rasht. Based on findings of research during 1345-85 qualitative and quantitative indicators of home have been improved. In spite of all internal and external constructions in city, there are still 8331 homeless families based on comprehensive results of General Census of Population and Housing of Rasht city in 1385. According to population estimations, resident families in Rasht will reach 225244 up until year 1400 and family aspect decrease to 3.36. Assuming that the favorite density is 1.1 families per each home, then needed homes for satisfying population demands will be 191457 units. At the end, according to existing potential in urban suburb of Rasht (ruined places) it is clear that using maximum of these places with a proper progressive pattern, part of future needs inside the city will be satisfied. The research method is descriptive-analysis. Manuscript profile -
Open Access Article
387 - Examine the effect of scientific optimism and organizational-citizenship behavior (OCB) and the mediating role of organizational commitment on the job motivation of high school teachers (Ramhormoz)
abdallah mackvandi frah naderi behnam makvandi Reza Pasha parvin Ehtesham zadehThe aim of this study was to present to examine effect of scientific optimism and organizational citizenship behavior and the mediating role of organizational commitment on the job motivation of teachers.The statical population of this study consists of all high school MoreThe aim of this study was to present to examine effect of scientific optimism and organizational citizenship behavior and the mediating role of organizational commitment on the job motivation of teachers.The statical population of this study consists of all high school teacher in Ramhormozcity in the acadaemic year of 2016-2017. Their number is 701. The sample was 250 (125female and 125 male) teachers,using the Korgesi and Morgan's tables were selected and they selected by stratified random sampling method, in the academic year of 2016-2017. The study was applied and research method was correlation using structural equations.The measurement tools used were Herzberg Job Motivation Questionnaire(1966),Hoy Scientific Optimism Questionnaire(2005),Oregon and Kanovsky(1996) OCB Questionnaire(1996),and Allen and Meyer(1990) Organizational Commitment Questionnaire.The data were analyzed using SPSS and Amos18 software and Coefficients and structural equation modeling were used for data analysis.The findings in the direct paths of the model indicated significant positive direct effect of scientific optimism on emotional commitment, significant positive direct effect of citizenship behavior on different aspects of organizational commitment (emotional and normative), significant direct effect of scientific optimism and organizational citizenship behavior on teachers' motivation, positive direct effect of emotional commitment and significant negative direct effect of continuous commitment on job motivation.Also in the intermediary path of the model,scientific optimism had positive indirect effects on job motivation, through emotional and normative commitment. Citizenship-organizational behavior had positive indirect and negative indirect effects on job motivation, respectively through emotional and normative commitment and a good fit analysis was created for the final model Manuscript profile -
Open Access Article
388 - الگوریتم رقابت استعماری (ICA) مبتنی بر روش بهینهسازی مخزن در سد کهیر
علی سردار شهرکی سمیه امایکمبود آب، به ویژه در ایران و در دوره خشکسالی­های اخیر، بر اهمیت دستیابی به یک سیاست عملیاتی بهینه برای مخازن بزرگ اهمیت پیدا کرده است. در دو دهه گذشته، بهینه­سازی سالانه مخازن در شرایط کنترل شده و همچنین شرایط آب و هوایی توجه بسیاری از محققان و کارشناسان را به خ Moreکمبود آب، به ویژه در ایران و در دوره خشکسالی­های اخیر، بر اهمیت دستیابی به یک سیاست عملیاتی بهینه برای مخازن بزرگ اهمیت پیدا کرده است. در دو دهه گذشته، بهینه­سازی سالانه مخازن در شرایط کنترل شده و همچنین شرایط آب و هوایی توجه بسیاری از محققان و کارشناسان را به خود جلب کرده است. در این مطالعه، رویکرد جدیدی برای پیش­بینی ذخیره مخزن ارائه شده است. الگوریتم رقابت استعماری (ICA) یک رویکرد جدید در زمینه محاسبات تکاملی است که راه حل بهینه را در مشکلات مختلف بهینه­سازی محاسبه می­کند. این الگوریتم با مدل­سازی ریاضی فرآیند تکامل اجتماعی روانشناختی، رویکرد جدیدی را برای حل مشکلات بهینه­سازی ریاضی ارائه می­دهد و در مقایسه با سایر الگوریتم­ها، سرعت مناسب و سرعت همگرایی بالایی را در یافتن پاسخ بهینه دارد. در این تحقیق از الگوریتم رقابتی امپریالیست برای بهینه­سازی سالانه مخزن کهیر برای به دست آوردن سیاست­های بهینه استفاده شده است. عملکرد هدف از جهت دستیابی به آب در پایین دست نیاز به ایجاد روابط براساس استمرار وجود دارد. عملکرد هدف از جهت دستیابی به آب در پایین دست نیاز به ایجاد روابط براساس استمرار دارد. مقایسه مدل ICA در جمع 100 نشان داد که الگوریتم ICA با میانگین بهترین ارزش تابع هدف 125، 6/114 و 60/85 با تعدادی از ارزیابی­های بیشتر تابع هدف برای دستیابی به ظرفیت بالاتر، پاسخ بهینه است. نتایج حاکی از خطای 1/6 درصدی در اجرای الگوریتم ICA بین انبارهای مشاهده شده و پیش بینی شده است. نتایج استفاده از الگوریتم رقابتی امپریالیست برای مسئله بهینه­سازی سالانه بیانگر توانایی روش پیشنهادی است. Manuscript profile -
Open Access Article
389 - پیشبینی صادرات زعفران ایران با مقایسه الگوریتم های یادگیری ماشین
علیرضا امیرتیموری منصور صوفی مهدی همایونفر مهدی فداییواردات و صادرات در همه کشورها نقش مهمی در رشد اقتصادی ایفا میکنند. بنابراین، انتخاب محصولات مناسب، باعث افزایش رقابتپذیری کشور در تجارت جهانی میشود. زعفران یکی از مهمترین و متمایزترین محصولات غیرنفتی ایران برای صادرات است. هدف این مطالعه، پیشبینی صادرات زعفران از ط Moreواردات و صادرات در همه کشورها نقش مهمی در رشد اقتصادی ایفا میکنند. بنابراین، انتخاب محصولات مناسب، باعث افزایش رقابتپذیری کشور در تجارت جهانی میشود. زعفران یکی از مهمترین و متمایزترین محصولات غیرنفتی ایران برای صادرات است. هدف این مطالعه، پیشبینی صادرات زعفران از طریق سه الگوریتم دادهکاوی و انتخاب الگوریتم مناسب در پیشبینی است. دوره نمونه مدلهای پیشبینی شامل دادههای صادرات زعفران ایران از سال ۲۰۱۲ تا ۲۰۱۹ است که از انجمن زعفران ایران جمعآوری شدهاند. پس از انجام مراحل آمادهسازی داده، پیشبینی صادرات زعفران با استفاده از سه الگوریتم دادهکاوی شامل شبکه عصبی مصنوعی، یادگیری عمیق و درخت تقویت گرادیانی انجام شد. برای انتخاب یک مدل پیشبینی بهتر، اعتبار مدل نقش مهمی ایفا میکند. صحت پیشبینی سه مدل طراحی شده به کمک خطای مطلق ( 036/0 = شبکهی عصبی مصنوعی، 031/0 = یادگیری عمیق شبکه، 047/0 = درخت تقویت گرادیانی)، معیار R2 (045/0 = شبکهی عصبی مصنوعی، 044/0 = یادگیری عمیق شبکه، 073/0 = درخت تقویت گرادیانی) و همبستگی (95/0 = شبکهی عصبی مصنوعی، 98/0 = یادگیری عمیق شبکه، 97/0 = درخت تقویت گرادیانی) اندازهگیری شدند. براساس یافتهها، تمامی این سه مدل طراحی شده دقیق هستند و خطای پیشبینی آنها بسیار کم و نزدیک به هم است. اما با تفاوت ناچیز، شبکه یادگیری عمیق کمترین خطا را دارد. نتایج میتوانند برای برنامهریزی دقیقتر صادرات زعفران مفید باشند. Manuscript profile -
Open Access Article
390 - پیش بینی میزان بولدر تولید شده حاصل از انفجار با استفاده از رگرسیون چند متغیره- مطالعه موردی: معدن سنگ آهن گل گهر
مجید غیاثی حامد شمس الدینی محسن طاهری مقدر اسحاق پورزمانی -
Open Access Article
391 - The Impact of Organizational Cynicism on Quality of Service Provision with Mediating Role of Job Satisfaction and Moderating Role of Organizational Identity
mostafa alirezaei ameneh malmir hamideh abbasiObjective: The present study aimed at analyzing the impact of organizational cynicism on the quality of service delivery with the mediating role of job satisfaction and moderating the role of organizational identity in Hamadan Health Insurance Organization.Design / Meth MoreObjective: The present study aimed at analyzing the impact of organizational cynicism on the quality of service delivery with the mediating role of job satisfaction and moderating the role of organizational identity in Hamadan Health Insurance Organization.Design / Methodology / Approach: The study is purposeful, applied, and descriptive in terms of data collection. The statistical population of this study includes all managers and staff of Hamedan Health Insurance Company. Using Cochran formula, 188 people were selected as the statistical sample by systematic random sampling. To measure the validity of questionnaires by face and content method and to determine the reliability of Cronbach's alpha which was estimated 0.786. For analyzing data from structural equation modeling, Smartphone software. L. SS version 2 was used.Results: The results showed that organizational cynicism had a significant effect on service quality, organizational cynicism on job satisfaction; job satisfaction on quality of service; organizational identity had a significant effect on service quality.Limitations and Consequences: Due to the multitude of research variables and given the specific complexity of the research, other variables for future research should be carefully examined both in the present statistical population and in other organizations rather than other meaningful relationships. To be more transparent and comprehensive. Manuscript profile -
Open Access Article
392 - Investigating the Mediating Role of Organizational Pessimism in the Relationship Between Incivility in the Workplace and Organizational Silence
Majed Maharani Barzani Mehrdad Sadeghi Ali RashidpourThe aim of the present study is to investigate the mediating role of organizational cynicism in the relationship between incivility in the workplace and organizational silence. The statistical population of this study was all the employees of the universities of Chaharm MoreThe aim of the present study is to investigate the mediating role of organizational cynicism in the relationship between incivility in the workplace and organizational silence. The statistical population of this study was all the employees of the universities of Chaharmahal and Bakhtiari provinces, whose number is 2255, according to the size of each region Using Cochran's formula, a sample size of 660 people was selected, and the sample people were selected using the stratified sampling method according to the size of each stratum. To collect the required data in this research, standard questionnaires were used and their validity and reliability were tested, and they were highly valid and reliable. In order to answer and check the hypotheses of the research, PLS-warp software was used to check the structural equations and path analysis using the partial least squares method. The results of the analysis conducted in the research showed that impoliteness in the work environment has a significant and positive effect on organizational silence, the coefficient of which is 0.77. And according to the output of Warp software, incivility in the workplace has a significant positive effect on organizational pessimism, the coefficient of which is 0.66, and also the effect of incivility in the workplace on organizational silence through organizational pessimism is positive with the coefficient of 0.88. Manuscript profile -
Open Access Article
393 - Investigating Managerial Myopia on Micromanagement and Analyzing the Mediating Role of Managers' Behavioral Tendencies (Case Study: Lorestan Province Government Organization)
Ali Shariatnejad Rezvan MennatiThe present study was conducted with the aim of investigating the effect of managerial myopia on the micromanagement, with the mediating role of behavioral biases. This research is based on practical purpose and descriptive-survey in terms of method. The statistical pop MoreThe present study was conducted with the aim of investigating the effect of managerial myopia on the micromanagement, with the mediating role of behavioral biases. This research is based on practical purpose and descriptive-survey in terms of method. The statistical population of the research is the government organizations of Lorestan province. Considering that the size of the statistical population is limited and specific, Cochran's sampling formula was used to determine the sample size, and at the 95% confidence level, the sample size was 384 people and were selected by available sampling method. In the current research, standard questionnaires were used to collect data, and their validity and reliability were confirmed by content validity method and Cronbach's alpha. Structural equation modeling and PLS software were used to test hypotheses and analyze data. The findings of the research show that managerial myopia has a positive and significant effect on the micromanagement of government organizations. Also, the findings show that managerial myopia has a positive and significant effect on the behavioral tendencies of government organizations. Manuscript profile -
Open Access Article
394 - Investigating the relationship between organizational rudeness and organizational silence with the mediating role of organizational cynicism
وحید میرزایی sakine davoodiReducing the areas of organizational silence of employees and their participation in work is one of the concerns of management in today's organizations. Therefore, the present study was conducted to investigate the relationship between incivility in the workplace and or MoreReducing the areas of organizational silence of employees and their participation in work is one of the concerns of management in today's organizations. Therefore, the present study was conducted to investigate the relationship between incivility in the workplace and organizational silence, and the mediating role of organizational cynicism. The present study has a practical purpose with field data collection method and a descriptive correlational method in terms of implementation method is used. The statistical population of this study was a staff of Payam-e-Noor University of North Khorasan Province. As the population was limited, the census method was used. The method of data collection was a questionnaire, for this purpose four standard questionnaires were used. The reliability of the questionnaire was evaluated by using Cronbach's alpha coefficient and confirmatory validity. Structural equation modeling and AMOS24 software were used for statistical analysis of the collected data. The results showed that there is a direct and significant relationship between incivility in the workplace and organizational silence. The results also showed that organizational cynicism mediates the relationship between incivility in the workplace and organizational silence. According to the research findings, it can be concluded that by reducing the incidence of organizational incivility and organizational cynicism of employees, staff silence is also reduced. Manuscript profile -
Open Access Article
395 - The effect of incivility in the work environment on deviant behaviors in the work environment with the mediating role of organizational pessimism and emotional exhaustion (case study: Isfahan Islamic Azad University (Khorasgan))
Abbas Ghaedamini Harouni Reza Ebrahimzadeh Dastjerdi Mehrdad Sadeghi de cheshmehThe purpose of this study was to investigate the impact of incivility in the workplace on deviant behaviors in the workplace with the mediating role of organizational pessimism and emotional exhaustion. The current research was applied in terms of its purpose and descri MoreThe purpose of this study was to investigate the impact of incivility in the workplace on deviant behaviors in the workplace with the mediating role of organizational pessimism and emotional exhaustion. The current research was applied in terms of its purpose and descriptive in terms of the method of collecting correlational data. The statistical population of the present study consisted of all the employees of Isfahan branch of Islamic Azad University (Khorasgan) in the number of 660 people, and 445 people were selected as a sample through the stratified sampling method proportional to the volume through Cochran's sampling formula. The research tools were Cortina et al.'s workplace incivility questionnaire (2001), Spector et al.'s deviant behavior questionnaire (2006), Dean et al.'s (1998) organizational cynicism questionnaire, and Maslach and Jackson's emotional exhaustion questionnaire (1981). Based on this, the content, form and construct validity were examined and after the necessary terms, the validity was confirmed and on the other hand, the reliability of the questionnaires was 0.90, 0.90, 0.88 and 0.88 respectively with Cronbach's alpha method. Estimated. Data analysis was done at two descriptive and inferential levels including structural equation modeling.The results of the research showed that incivility in the workplace had a positive effect on deviant behaviors in the workplace, and the coefficient of this effect was 0.77, and also, the results showed that organizational pessimism and emotional exhaustion play a mediating role between incivility in the workplace and deviant behaviors. had in the work environment. Manuscript profile -
Open Access Article
396 - Evaluation of management forecasts in corporate capital increase justification reports
صغری عابدی mohammad hossain gaemi taher eskandarliInvestment decisions require corporate executives to anticipate the future performance of the company in the form of a capital increase justification plan.. Although these predictions are an important factor in the success of an investment, they are not directly observa MoreInvestment decisions require corporate executives to anticipate the future performance of the company in the form of a capital increase justification plan.. Although these predictions are an important factor in the success of an investment, they are not directly observable by external stakeholders. The purpose of this study is to evaluate the accuracy of management forecasts of revenue and operating profit of the company in the explanatory reports of capital increase of companies. In this regard, the accuracy of capital increase forecast with the variables of company size, return on assets, financial leverage, property rights, floating stocks and capital increase ratio has been examined. To review the research, a sample consisting of 184 companies listed on the Tehran Stock Exchange in the period 2007 to 2020 was selected and the data were analyzed using regression. The results show that there is a significant direct relationship between firm size variable and book value of owners' rights inversely related to operating profit, but there is a significant relationship with independent research variables including firm size, return on assets, leverage. Financial, book value of equity and floating stocks were not observed with the dependent variable of operating income. Manuscript profile -
Open Access Article
397 - بررسی تأثیر رفتار شناسی مالی بر ظهور بازارهای سرمایهای (بیمه و سهام)
مصطفی حیدری هراتمه -
Open Access Article
398 - بررسی جذب سطحی کربن مونوکسید، هیدروژن و متان بر روی غربال مولکولی کربنی
حمیدرضا بزرگ زاده زهرا موسوی محمدرضا قاسمی -
Open Access Article
399 - بررسی ریز ساختار پلی اتیلن سبک به روش طیف بینی زیر قرمز و جزء به جزء کردن شویشی دمای افزاینده
حسین مهدوی مجتبی عنایتی نوک -
Open Access Article
400 - بررسی برهمکنش مواد فعال سطحی دوپیکره و مواد رنگزای آلی برای افزایش حلالیت رنگ در میسلهای مواد فعال سطحی
سارا فاضلی بهشته سهرابی -
Open Access Article
401 - The role of political and economic uncertainties on improving the predictability of industrial activities in Iran
Farzaneh Khalili mehdi mohammadi farid asgariThe industrial sector and its growth is one of the most important performance indicators of the economy at the macro level and achieving a higher growth rate in this sector is one of the important goals of any economic system. Therefore, it is important to study the fac MoreThe industrial sector and its growth is one of the most important performance indicators of the economy at the macro level and achieving a higher growth rate in this sector is one of the important goals of any economic system. Therefore, it is important to study the factors that affect the development of the industrial sector and improve the predictability of this sector. A review of the literature on the development of industry in the economy shows that one of the most important factors affecting its development is the stability of macroeconomics in both economic and political sectors, so that economists today have accepted that economic and political stability is a necessary condition for growth. It is high and continuous in the industry sector of the economy. In this regard, in the present study, the role of political and economic uncertainties on improving the predictability of industrial sector activities in Iran during the period 1991 to 1399 has been investigated. GMM generalized torque method was used to analyze the data. Findings showed that economic and political uncertainties have had negative and significant effects on the development of the industrial sector in Iran. It was also observed that considering political and economic uncertainties can improve the predictability of industrial sector activities. Accordingly, it is concluded that macroeconomic and policy policies in the country should be implemented a way that does not harm economic stability and thus the development of the industrial in the country. Manuscript profile -
Open Access Article
402 - Forecasting the price of electricity in the cash and advance markets and designing the optimal model for selling electricity in the mentioned markets with the Copola function approach.
Arash Jalebi mahmood khodam hossein mohammadnezhadThe purpose of this article was to predict the price of electricity in the cash and cash markets and to design the optimal model of electricity sales in the aforementioned markets with the Copula function approach. For this purpose, daily information was used in the per MoreThe purpose of this article was to predict the price of electricity in the cash and cash markets and to design the optimal model of electricity sales in the aforementioned markets with the Copula function approach. For this purpose, daily information was used in the period of 1396-1401. In order to forecast, time series models and OLS, GARCH and Copula approaches were used. The results showed that trigonometric functions can well explain the behavior of electricity prices, which is caused by the seasonal behavior of electricity prices during one-year periods. In the random part, the estimated values show that the random component has an average of almost zero and the speed of returning to the average in prices is high. The average of the shocks, their negativity and variance are very small. The small average values of the shocks actually show that the shocks that occurred in the price of the electricity market in Iran are very insignificant and more importantly, these shocks were more of the negative type. Regarding the optimal strategy when entering into futures transactions, our advice to players is to use the Copula-Garch method to calculate the optimal ratios for risk hedging, for two reasons. The need for risk hedging is less and as a result the transaction cost is lower, secondly, due to the existing restrictions and especially the low liquidity in energy exchange transactions, it is practically possible to cover more risk than the cash position Manuscript profile -
Open Access Article
403 - Presenting a model for predicting the price of digital currency in conditions of environmental uncertainty with a fuzzy artificial neural network
mohammad hasan darvish motevali shirin aminiAbstarctIn this research, using the method of fuzzy neural networks, the price of Bitcoin is predicted. In order to identify the appropriate criteria in this research in order to predict the price of Bitcoin, we have used previous studies and researches in this field in MoreAbstarctIn this research, using the method of fuzzy neural networks, the price of Bitcoin is predicted. In order to identify the appropriate criteria in this research in order to predict the price of Bitcoin, we have used previous studies and researches in this field in the first stage. In the following, using interviews with experts and experts in this field, the available information about Bitcoin became the final factors. Research information was collected using related sites and identified criteria. In this way, we first normalized the collected data. In the next step, by entering the normalized information into the MATLAB software and using the designed toolbox and using the fuzzy neural network method, Bitcoin price was predicted. In this way, 60% of the input data, which includes 1330 data, was considered as training data and 40% of the data, which is 887 data, was considered as testing. The research results show high accuracy prediction using the proposed method. As the error was considered in two cases, a small value was calculated for the error of the method. Keywords: prediction, bitcoin price, fuzzy neural network. Manuscript profile -
Open Access Article
404 - optimal model sales in gold ounce and s&p 500 markets on the basis of optimal stopping
amir mahmoudian maryam khalili araghi hamidreza vakilifardExtended Abstract Throughout history, predicting price in financial markets has always been of high interest to financial activists and analysts. Recently, various methods have been proposed and adopted to predict the dynamism of financial markets using time series o MoreExtended Abstract Throughout history, predicting price in financial markets has always been of high interest to financial activists and analysts. Recently, various methods have been proposed and adopted to predict the dynamism of financial markets using time series of records of prices. However, high-precision predication of financial prices is still a deemed long-term challenge that constantly call for state-of-the-art approaches. Purpose Thus, the purpose of the current study was to examine the efficacy of optimal stopping, also known as early stopping and use its connection with branching processes to predict the optimal buying and selling prices in several financial markets. gold ounce market and S&P 500 index have been predicted in short term and long-term frameworks on the basis of fixed horizon. And for each. frame work, different time frames have been selected. Closing price data from 1995 to 2022 have been used for every time frame. Methodology Advanced methods for optimal stopping include approximating the value function and then using that approximation in a policy. Although such policies can work very well, they are generally not guaranteed to be interpretable (Siokan and Mišić 2020). On the other hand, some researchers have proposed that the optimal stop models are too complicated to solve well and the strategies of buying at a low price and selling at a high price are not very practical in this theory (Liu and Mo 2022). According to the issues raised, the researcher intends to use the optimal stop theory and its connection with branch processes to implement and examine this theory in a number of prominent international financial markets. In this research, we are going to use the optimal stop statistical theory to predict the time of buying and selling in these markets in an optimal way. Finding The optimal stopping algorithm seeks to determine the maximum value from a set of random variables that are exhibited in the order they are generated. Each variable should either be selected when exhibited or be skipped in favor of the next variable, and if all the variables till the nth variable are skipped, this variable is selected automatically. It should be borne in mind that the theory of optimal stopping first examines the previous data and finds out whether there is a divergence, according to which it determines which market cannot be predicted based on this theory. In general, these random variables are considered as independent and co-distributed. Yet, due to the complexity of this theory, even in this case, solving problems directly proves to be very difficult, and hence the correlation between this theory and branch processes are employed to simplify solution. The steps of this process are as follows: Step 1 The analyst finds the planning horizon (20 - horizon in the present paper) Step 2 Determine the statistical distribution of values using statistical tests, including the goodness of fit, chi-square, Chebyshev's inequality, and Q-Qplot (Moud et al. 1973) Step 3 Transforming it to a normal distribution using Box-Cox Transformations (Cox-Box 1964), and converting to the standard normal distribution (minus mean value divided by standard deviation) (Moud et al. 1973) Step 4 Using inverse distribution function (using probability integral transform theorem) (Moud et al. 1973) and transforming it to considered distribution in branching process and determining convergency or divergence of data (Ross 1983; Shishebor et al. 2004) Step 5 Predicting the best point for optimal buy or sell at a determined horizon (Assaf et al. 2000) Step 6 Reversing all transforms and predicting real values (Assaf et al. 2000) Conclusion The results indicate that by optimal stopping for short term framework, S&P 500 index indicates %67 success and gold ounce shows %53 success in the prediction of prices. In long term framework, S&P 500 index's success equals to %68 and gold ounce equals to %85 in prediction of prices. The obtained results show that the optimal stop theory has performed better in predicting the gold price in the long-term time frame and the S&P 500 in the short-term time frame. The S&P 500 market and the gold market have obtained the most predictability based on the optimal stop theory. This can be confirmed by market traders because the S&P 500 and gold market are interesting markets from a technical and trading point of view. The number of transactions and high liquidity and the difference in spread and commission in these two markets compared to other markets can be indicative of this. Also, the high volatility in the two mentioned markets due to the uncertainty regarding the continuation of prices and key economic indicators presents countless opportunities to traders. According to the obtained results, the optimal stopping can be used as a trading and analytical indicator. Also, the characteristic of optimal stopping is that based on historical data, it shows the prediction as the optimal point (buying and selling price) in the future. Due to the fact that examining the financial markets both from the study and analytical point of view and from the trading point of view by using a variety of forecasting patterns and indicators requires understanding the possibilities of market behavior, choosing a time frame and having a strategy. Manuscript profile -
Open Access Article
405 - To Study the Effect of Characteristics of Corporate Governance on the Quality of Financial Reporting (Evidence from Tehran Stock Exchange)
Roya Darabi Mahnaz PiriThis research studies the effect of Corporate Governance on quality of financial reports of admitted companies in Tehran Stock Exchange in a 7-year period from 2006 to 2012. It is expected that establishment of appropriate Corporate Governance would prevent decrease in MoreThis research studies the effect of Corporate Governance on quality of financial reports of admitted companies in Tehran Stock Exchange in a 7-year period from 2006 to 2012. It is expected that establishment of appropriate Corporate Governance would prevent decrease in quality of financial reports along with making financial reporting process more controllable. In the present research we have used preciseness of prediction of future operational cash currents via operational profit elements as a measurement index from evaluation of financial reporting quality and also relation of off-duty members of board of directors, organizational investors owned share, power concentration, board of directors size, ownership structure, type of ownership, free floating share percentage, auditing quality, internal auditing, financial reporting quality and auditing period were used as Corporate Governance. A total number of 100 companies were selected as sample companies and using comparison test of average of the two societies we would analyze the results. The results achieved from the research indicated that ability index of Corporate Governance which consists of all structural specifications studied in this research is not effective on the quality of financial reporting of the companies admitted in Tehran Stock Exchange. Also in studying the effect of Corporate Governance individually it was observed that only quality of auditing reporting would affect the quality of financial reporting of the companies. Manuscript profile -
Open Access Article
406 - A comparison between,CAPM,Fama and French,s models and artificial neural networks in predicting the Iranian stock Market
S.M Jafari جواد Misaghi میثم AhmadvandComparison between the Capital Asset Pricing model,Fama and Ferench three factors model and Artificial Neural Network model in predicting Tehran stock Exchange returns is discussed in this research.the first two models are linear and the following are nonlinear.Four hyp MoreComparison between the Capital Asset Pricing model,Fama and Ferench three factors model and Artificial Neural Network model in predicting Tehran stock Exchange returns is discussed in this research.the first two models are linear and the following are nonlinear.Four hypotheses have been designed for this purpose.To examine these hypotheses,the expected return was calculated daily during 1383 to 1387 for 110 companies.companies in each quarter have divided to 6 portfolios by size and book to market value factors. Results showed that the performance of Fama &Ferench three factors model is better than Capital Asset pricing model.Also Univariable and Multyvariable Artificial Neural Network models have better performance in compare with their corresponding nonlinear models. Manuscript profile -
Open Access Article
407 - Using Smooth Transition Regression (STR) to predict Business Cycles
Harmony Shahmoradi Hamid Abrishami Oranus ParivarForecasting business cycles is very important in macroeconomic and it is an important part in process of economic decision-making and policy. In recent years, non-linear models have been considered more for forecasting economic variables and application of these models MoreForecasting business cycles is very important in macroeconomic and it is an important part in process of economic decision-making and policy. In recent years, non-linear models have been considered more for forecasting economic variables and application of these models has been made a significant improvement in modeling of the behavior of variables in the area of macroeconomic and particularly financial economics. This article provides a convenient and powerful model for forecasting business cycles by using smooth transition regression (STR). The results show that very little error that indicates model performance is acceptable. Manuscript profile -
Open Access Article
408 - The Relationship Between Cash Flow Forecasting and Cost of Owners’ Equity
Ali Baghani narges ghorbani Cash flow forecasting is an important factor in many economic decisions because cash flows play an important role in almost all decision making by groups such as securities analysts, creditors and managers (Sloan, 1996). To discover this fact, the relationship b More Cash flow forecasting is an important factor in many economic decisions because cash flows play an important role in almost all decision making by groups such as securities analysts, creditors and managers (Sloan, 1996). To discover this fact, the relationship between the cash flow forecasting and the cost of owners’ equity was investigated. In this study, using the data analysis, the relationship between cash flow forecasting and cost of owners’ equity was examined. The statistical sample of research consisted of 167 companies listed in Tehran Stock Exchange during the 6 years and a multivariate regression method were used to test the hypotheses for gathering information. Test of the hypothesis and finally analysis of the data were done using Excel software as well as statistical software Spss23, Eviews9, Minitab19.The following models have been used to test the hypothesis according to Sang Hwan Yaongs paper (2015). According to the number of variables studied, multiple regression was used. The results of the research show that there is no significant relationship between cash flow forecasts and the cost of owners’ equity. Manuscript profile -
Open Access Article
409 - Man in the Worldview of Shams-e Tabrizi
Soniya Farhang Farrahi Soheilā Mousvi SirjāniIndividual or collective worldview includes individual or a group attitudes about the universe, the creator of the universe and mankind. The significance of the worldview comes from the fact that the actions of human beings are based on their worldview. In the book Maqa MoreIndividual or collective worldview includes individual or a group attitudes about the universe, the creator of the universe and mankind. The significance of the worldview comes from the fact that the actions of human beings are based on their worldview. In the book Maqalat-e Shams-e Tabrizi (Discourse of Shams-e Tabrizi), as the remnants of Shams-e Tabrizi, there are many points and issues that help us to know his worldview. The purpose of this article is to explain Shams’ view about humanity as one of the foundations of his worldview. In order to obtain a precise result, all the parts of Maqalat have been examined, and all arguments have been based on his words in the book. The mystics focus on man in three areas of "man and self, man and God, and man and his fellow men", so this research includes the important words of Shams in the three above-mentioned fields. In this article, the prominent position of man in the thoughts of Shams has been shown, the position which is based on his view about ‘unity of Being’. Also, his serious and responsible attention to all human beings (and not just the perfect man) has been considered. Manuscript profile -
Open Access Article
410 - The Conceptual Metaphors of Lam’at
Samirā Bakhtiyārinasab Kheirollāh MahmoodiThe intellectual system of any text can be described by analyzing its conceptual metaphors. The aim of the present study is to find the structures derived from the conceptual metaphors of Lam’at (Divine Flashes), written by Fakhr al-Dīn Ibrahīm Irāqī. These struct MoreThe intellectual system of any text can be described by analyzing its conceptual metaphors. The aim of the present study is to find the structures derived from the conceptual metaphors of Lam’at (Divine Flashes), written by Fakhr al-Dīn Ibrahīm Irāqī. These structures represent the intellectual system of Lam’at. To this end, first, the conceptual metaphors of the text are identified by careful examination of its language. Next, the structure derived from the conceptual metaphors of the text, which functions as a mirror reflecting its worldview, is described by analyzing the metaphors and finding the links among them. The four main pillars of Lam’at and Fakhr al-Dīn Ibrahīm Irāqī's thought are these conceptual metaphors: ‘God is love’, ‘love is the king’, ‘love is the Sun’ and ‘love is a mirror’. In addition to the links among these four metaphors, the conceptual metaphor ‘love is human’ plays a key role in linking the four conceptual metaphors to each other and shows the intellectual level of Lam’at. There are other conceptual metaphors in Lam’at, each of which describes the worldview of its author, but the abovementioned five metaphors are more pivotal. Manuscript profile -
Open Access Article
411 - شاعر غربت(تاملی در نوستالژی و نومیدی های شعر اخوان ثالث)
عباس باقی نژاد -
Open Access Article
412 - نقد تطبیقی اسطوره آفرینش در شاهنامه فردوسی و مهابهاراتای هندی
فاطمه پاکرو -
Open Access Article
413 - The Outlook of Mulānā Jalāl-al Din Rumī and Plotinus: A Comparative Study
Hamidrezā KharazmiOutlook, as the human view to world and himself/herself, provides answers to the fundamental questions of man about the world, the creation of world, the situation of creatures in the world, the position of man in the world, the afterlife world and the end of existence. MoreOutlook, as the human view to world and himself/herself, provides answers to the fundamental questions of man about the world, the creation of world, the situation of creatures in the world, the position of man in the world, the afterlife world and the end of existence. Plotinus, one of the thinkers of the 2th century, has opened a new way in philosophy. Mulānā Jalāl-al Din Rumī, the Persian poet and mystic of the 12th century, based on his mystical outlook, has a special view regarding being and world. The main question of the present article is about how these two thinkers view existence and being. For answering the question, at first, we analyze their ideas about world-view and then study the similarities and differences of them. Manuscript profile -
Open Access Article
414 - انعکاس اندیشه خیام در آثار سعدی
فریده محسنی هنجنی -
Open Access Article
415 - The Outlook of Rūmī and the Function of Quranic Verses and Hadiths in Masnavi Mulavi; a Study Based on the Transitivity System
Ashraf Sheibāni Aghdam Mohammadali Ghozashti Rāheleh GholāmiThe present article focuses on the relationships among choices, linguistic models, ideologies and the power of hidden connections in Masnavi Mulavi. The article considers Jalāl ad-Dīn Muhammad Rūmī’s dealing with values and main thoughts expressed in Quranic verse MoreThe present article focuses on the relationships among choices, linguistic models, ideologies and the power of hidden connections in Masnavi Mulavi. The article considers Jalāl ad-Dīn Muhammad Rūmī’s dealing with values and main thoughts expressed in Quranic verses and Hadith based on critical discourse analysis approach and Michael Halliday’s theory of the transitivity system of functional grammar. So, based on Halliday’s theory of systemic functional grammar, it is analyzed and categorized the couplets of Masnavi Mulavi which refer, implicitly or explicitly, to Quranic verses and Hadiths. The ideological contents of the couplets show that according to this mystical text, God’s will rules in all things. The core and the semantic center of processes used in the verses of Quran and Hadiths are “relational process”. On the other hand, the Verses and Hadiths including one distinct process can refer to several processes, or vice versa, several processes can be reduced to one. Thus, it is emphasized on educational aims. Manuscript profile -
Open Access Article
416 - Analysis of the Story of Fereydun; Based on His Dualistic Character
esmaeil narmashiriThe structure of the story of Fereydun shows that Ferdosi has narrated it with a dualistic view and in the form of fictional royal stories. By considering the deep structure of the story it shows clearly that Fereydun has a dualistic nature: a divine nature as well as a MoreThe structure of the story of Fereydun shows that Ferdosi has narrated it with a dualistic view and in the form of fictional royal stories. By considering the deep structure of the story it shows clearly that Fereydun has a dualistic nature: a divine nature as well as an evil one. His divine nature is manifested in his illuminated face, sense of justice, rationality and pacifism; afterwards these features are transferred to Iraj and Manuchehr who brings the evil age of Salm and Tur to an end. But Fereydun’s latent evil nature that is hidden beneath is suddenly revealed after returning his sons from Yaman. The evil nature appears in the form of dragon and has the following features: greed, avidity, treachery, irrationality, corruption and chaos. Afterwards, these features are transferred to Salm and Tur. Manuscript profile -
Open Access Article
417 - The Developmental Process of Types of Egocentrism Using Content Analysis of Children and Adolescents’ Books
Roghyeh BalaliThe development of different types of egocentrism were analysed on the basis of piagetian theory in the books published from 1996-1998 in four different age groups. The study was conducted through content analysis of a sample of 30 book titles selected from sources avai MoreThe development of different types of egocentrism were analysed on the basis of piagetian theory in the books published from 1996-1998 in four different age groups. The study was conducted through content analysis of a sample of 30 book titles selected from sources available at the Center for Intellectual Development of Children and Adolescents. Tabular and graphical representation of data were made using descriptive analysis. Results indicated: (1) In most books, specially those written by Iranian writers, different types of indirect egocentrism were portrayed, (2) Foreign writers have helped children to decentrate their egocentrism more than Iranian writers, (3) A very low level of inter-rated compatibility between judgments made by experts at the Supreme Council of Literature Research Documents could be attributed to the diverse view points of judges Manuscript profile -
Open Access Article
418 - Cognitive exhaustion and solving cognitive problems:testing the moderating effect model of dispositional optimism
Hosein Zare Ali Khodaei Omid Shokrihe aim of the present study was to investigate the moderating effect of dispositional optimism in the relationship between cognitive exhaustion and solving cognitive problems. Three hundred university students completed the Life Orientation Test- Revised (LOT-R, Schie Morehe aim of the present study was to investigate the moderating effect of dispositional optimism in the relationship between cognitive exhaustion and solving cognitive problems. Three hundred university students completed the Life Orientation Test- Revised (LOT-R, Schier, Carver & Bridges, 1994). Forty students whose scores on the dispositional optimism were two standard deviations above or below the mean score were selected and randomly assigned into four groups each including ten participants. In the first phase of the experiment, experimental and control groups confronted with uncontrollable and controllable discriminative tasks, respectively. In the second phase of the experiment, all participants in the problem solving situation, replied to the anagram task. The data were analyzed using the two-way between subjects analysis of variance. The results indicated that there was a significant main effect of group and dispositional optimism but there was no significant interaction between group and dispositional optimism. Therefore, the relationship between cognitive exhaustion and solving cognitive problems was not moderated by dispositional optimism. These findings suggested the role of cognitive exhaustion variability and dispositional optimism in predicting problem solving and that the causal relation between cognitive exhaustion and problem solving is not a function of dispositional optimism variation. Manuscript profile -
Open Access Article
419 - The Comparison of the Choice Theory and Optimism Training on Sense of Coherence Among Students
Reza Mahpouya Afsaneh GhanbariPanah Mansureh ShahriariAhmadi This study aimed to compare the effectiveness of the choice theory and optimism training on the sense of coherence among students. The research method was quasi-experimental with pretest-posttest design and control group and follow-up for two months. 120 female st More This study aimed to compare the effectiveness of the choice theory and optimism training on the sense of coherence among students. The research method was quasi-experimental with pretest-posttest design and control group and follow-up for two months. 120 female students were selected by convenience sampling method and responded to Sense of Coherence Scale (Antonovsky, 1987). Then 60 students with the lowest scores of the sense of coherence were randomly assigned to 3 groups including 2 experimental groups and one control group. The students of experimental groups participated in choice theory and optimism courses in 8 sessions. All the 3 groups were evaluated by post-test at the end of the courses and after 2 months in follow-up. The results showed that both choice theory and optimism training significantly increased sense of coherence among students, but choice theory training had more effectiveness. According to the findings of this study and the importance of the sense of coherence, both choice theory and optimism courses can be useful methods to educate students, but choice theory training is recommended as a more effective method. Manuscript profile -
Open Access Article
420 - Artificial neural networks:a modle for prediction
Hossein Pourshahriar Kzaem R. Tabatabaiei M. Karim Khodapanahi A. Kazemnejad Soraya KhafriTaking into account the ambiguities and limitations of prevailing statistical models, such as losing data related to complicated and nonlinear interactions between psychological constructs and some of the assumptions like homogeneity of variances and normal distribution MoreTaking into account the ambiguities and limitations of prevailing statistical models, such as losing data related to complicated and nonlinear interactions between psychological constructs and some of the assumptions like homogeneity of variances and normal distribution, the present research investigated the capability of Artificial Neural Networks Model for con ducting predictive studies. A sample of 456 male senior high school students responded to the California Personality Inventory (CPI; Gaff, 1975) and Adjustment Inventory for School Students (AISS; Sinha & Singh, 1993), and were categorized into five levels of adjustment (from maladjusted to completely adjusted). Factor analysis of various combinations of personality traits suggested that some of the networks could not predict adjustment due to non conformity between the number of variables and network architectures. However, a revision of the architectures and repetition of new networks significantly increased the proportion of correct predictions (the proportion of participants categorized into the indicated levels of adjustment based on AISS). The most appropriate network for predicting adjustment included a combination of the cognitive variables of flexibility, femininity, communality and tolerance. Manuscript profile -
Open Access Article
421 - The Mediating Role of Academic Optimism in the Relationship Between Mindfulness and Counterproductive Academic Behavior
Ebrahim Karimi Kian Solmaz Daneshmandi Mahmood Rostami Ehsan Keshtvarz KondaziThis study aimed to investigate the mediating role of academic optimism in the relationship between mindfulness and counterproductive academic behavior. The research method was correlational and participants were (143 male and 160 fe- male) secondary school students fro MoreThis study aimed to investigate the mediating role of academic optimism in the relationship between mindfulness and counterproductive academic behavior. The research method was correlational and participants were (143 male and 160 fe- male) secondary school students from Marvdasht city which selected via random multistage cluster sampling method. To examine research variables, all participants completed Mindfulness Scale (Droutman, Golub, Oganesyan, & Read, 2018), Academic Optimism Questionnaire (Tschannen-Moran, Bankole, Mitchell, & Moore ,2013) and Counterproductive Student Behavior Scale (Rimkus, 2012). Data were analyzed using structural equation modeling. The results showed that the direct effect of mindfulness on counterproductive academic behavior was not significant; but the direct effect of mindfulness on academic optimism and the direct effect of academic optimism on counterproductive academic behavior were significant; also, the effect of mindfulness on counterproductive academic behavior was mediated significantly by academic optimism. In general, the findings showed that the role of mindfulness and academic optimism in explaining counterproductive academic behavior. Based on these findings, it can be concluded that in order to reduce students’ counterproductive academic behavior, their academic awareness and optimism should be considered. Manuscript profile -
Open Access Article
422 - Evaluation of precipitation forecasts of WRF model for daily heavy rain in Qazvin Province during 2002-2011
F. Arkian N. Mashatan P. S. Katiraie Borojerdi E. Mirzaei Haji BaghloIn this study, the precipitation forecasts by WRF model for daily pervasive heavy rains in Qazvin province was evaluated. For this purpose, 30 cases of the heavy and pervasive rains in Qazvin province during (2002-2011) with two different configurations (KFMYJ, GDMYJ) s MoreIn this study, the precipitation forecasts by WRF model for daily pervasive heavy rains in Qazvin province was evaluated. For this purpose, 30 cases of the heavy and pervasive rains in Qazvin province during (2002-2011) with two different configurations (KFMYJ, GDMYJ) schemes by the WRF model at intervals of 24, 48 and 72 hours, have been simulated. Because of various heights and different climates of Qazvin and considering average rainfall, Qazvin was divided into five precipitation regions containing plain, plain margins, submontane, and mountains of Northeast and Southwest. Then with the two methods, point and areal, simulated rainfall and the corresponding observed values were evaluated. According to evaluated results, for GDMYJ configuration, root mean square error and bias multiple, with respective values of about 8.7 and 1.7 for 24-hour rainfall simulation are better than 48 and 72 hours. Also correlation coefficient between observations and model simulations of precipitation in the submontane region in comparison with other regions has slightly higher accuracy of approximately 0.5. In general, the fraction of systematic error to total error is very low and it is more due to random errors. Considering the rainfall threshold ≥10 mm and the 2×2 contingency tables for the occurrence or absence of precipitation, skill scores were calculated for the model in Qazvin region. The results showed that the model skill in predicting precipitation in 24, 48 and 72 hours on the threshold has acceptable accuracy and on average about 71% of cases were correctly predicted. Manuscript profile -
Open Access Article
423 - اثر مولفه شعاعی میدان تنش در پیش بینی شکست ترد در ناچ های V شکل تحت بارگذاری مود ترکیبی صفحهای
سید حسن سجادی احمدرضا خورشیدوند محسن جباری مهرداد جوادیمعیارهای مختلفی جهت پیش بینی شکست در ناچهای V شکل ارایه شده اند. این معیارها را می توان در سه گروه کلی انرژی مبنا، کرنش مبنا و تنش مبنا دسته بندی کرد. هر کدام از معیارهای موجود یک کمیت از جنس انرژی، کرنش و تنش را به عنوان عامل اصلی ایجاد شکست در نظر گرفته و بیان می کنن Moreمعیارهای مختلفی جهت پیش بینی شکست در ناچهای V شکل ارایه شده اند. این معیارها را می توان در سه گروه کلی انرژی مبنا، کرنش مبنا و تنش مبنا دسته بندی کرد. هر کدام از معیارهای موجود یک کمیت از جنس انرژی، کرنش و تنش را به عنوان عامل اصلی ایجاد شکست در نظر گرفته و بیان می کنند هنگامی که این کمیت به مقدار بحرانی خود برسد، شکست در جهت بیشینه مقدار کمیت مورد نظر اتفاق می افتد. اغلب معیارهای تنش مبنا مولفه مماسی میدان تنش را به عنوان کمیت اصلی موثر در ایجاد شکست در نظر میگیرند. اما در معادلات انرژی مبنا و کرنش مبنا به طور ناخواسته مولفه تنش شعاعی نیز در معادلات وارد می شوند. در این پژوهش با مطالعه معادلات و نتایج یک معیار انرژی مبنا و یک معیار کرنش مبنا و مقایسه آن ها با یکدیگر نحوه اثرگذاری مولفه تنش شعاعی در دقت پیش بینی ها مورد بررسی قرار می گیرد. Manuscript profile -
Open Access Article
424 - Analyzing the legal rules governing the remedy caused by the termination of the contract and predicting its breach with emphasis on international documents
hadi roosta sjafar hashemi امیر محمد sediqianField and Aims: Today, businessmen in their international exchanges often use the contract of sale, which is sometimes breach by one of the parties, And inevitably, to compensate for the damage, compensation methods should be used in different systems of the world. In t MoreField and Aims: Today, businessmen in their international exchanges often use the contract of sale, which is sometimes breach by one of the parties, And inevitably, to compensate for the damage, compensation methods should be used in different systems of the world. In this regard, compensation for contractual damages has been fully accepted in most legal systems and international documents, which include the principles of European contracts and the principles of international commercial contracts, as well as the Convention on the International Sale of Goods But in Iran, internal legal rules are still used when necessary which has caused legal challenges in this regard.Method: The present research was carried out with a descriptive analytical method.Finding and Conclusion: The findings of the present research showed that the principles of international documents that are important in the enactment of laws and principles governing contracts in terms of anticipating violations and termination and finally compensation have not been included in the legal rules of the subject as it should be, because the review and analysis The assessment of damages caused by breach of contract in Iranian law compared to international documents indicates the weakness of Iran's legal system, as a result of the need for Iran's judicial system to apply international principles and documents and legal rules governing contracts in line with commercial and economic interactions at the international level. And compensation for damages caused by breach of contract is necessary. Manuscript profile -
Open Access Article
425 - نقش قابل پیشبینی بودن خسارت در مسؤلیت مدنی قراردادی و قهری
محسن قاسمی -
Open Access Article
426 - زمینه های بدبینی و یأسِ فلسفی در اندیشه و آثار میرزاده ی عشقی
علی اصغر حلبی علی بالی -
Open Access Article
427 - مقایسه قدرت پیش بینی منحنی فیلیپس کینزین جدید هایبریدی و مدل ARIMA از تورم
زهرا افشاری مرضیه بیات -
Open Access Article
428 - The Application of GMDH Neural Network Approachin Forecasting the Price of Soybean Meal in Merchendis Stock Exchange
علی اکبر باغستانی سعید یزدانی مجید احمدیانAbstract Livestock and poultry industry has depended much on soybean meal. This dependence has led to fluctuations in the price of this product and therefore, forces market participants to follow the sensitivity and accuracy. These fluctuations created serious concerns MoreAbstract Livestock and poultry industry has depended much on soybean meal. This dependence has led to fluctuations in the price of this product and therefore, forces market participants to follow the sensitivity and accuracy. These fluctuations created serious concerns about the supply and price of soybean meal. So, this study, using monthly and weekly data of Soybean prices in the exchange market, tried to forecast soybean price. So Soybean Meal price has predicted with neural network GMDH algorithm and ARIMA. The results based on the root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MPAE) showed that the GMDH algorithm, has a better ability to predict the price accurately. Manuscript profile -
Open Access Article
429 - Predict the effect of macroeconomic variables on stock price index using neural network GMDH
امید Farman ara وحید Farman araThe economy of every country is composed of different parts, the relationship among which determines the economics direction of that country. The capital market together with money market make up the financial market as the fundamental basics of an economy. Their operat MoreThe economy of every country is composed of different parts, the relationship among which determines the economics direction of that country. The capital market together with money market make up the financial market as the fundamental basics of an economy. Their operation has significant influence on the growth and development of the economy. In cases there is no constructive relationship between the financial market and other parts of the economy, economic performance might be subject to distortions. The stock market as a fundamental basic of the financial market has a crucial role in facilitation of investments in the capital market. Given the importance of expectations in different economic fields, the main purpose of this study is to project behavior of the Tehran stock exchange price index. Therefore, after a review of dominant economic theories, we use a new method, artificial neural network GMDH, to forecast the impact of macroeconomic variable on the Tehran stock exchange price index. The GMDH Algorithm is a nonlinear model to anticipate complex systematic relationships between variables of the model. The special feature of this deductive algorithm is recognition and screening of the most effective variable to estimate the model with training samples and omit the non-significant ones the simulation process with testing samples. So, we can solve the model via iterative methods to minimize the typical standard Error like RMSE, MAPE, and so on. Manuscript profile -
Open Access Article
430 - بررسی پدیده خنثایی پول در اقتصاد ایران
مهدی حنطه منوچهر عسکری محمود ختایی -
Open Access Article
431 - ارزیابی مدلهای خطی و غیرخطی در پیشبینی شاخص قیمت سهام در بورس اوراق بهادار تهران
علی اکبر خسروی نژاد مرجان شعبانی صدر پیشه -
Open Access Article
432 - Chaos and Nonlinear Stock Price Index of Tehran Stock Exchange Chaos and Nonlinear Stock Price Index of Tehran Stock Exchange
قدرت اله امام وردی سمانه صفرزاده بیجار بنهAbstract The stock price indices are indispensable variables in economic systems, these usually complicated time series are almost stochastic, and hence their variation is assumed unpredictable. For this purpose, nonlinear and predictable examinations are used to test MoreAbstract The stock price indices are indispensable variables in economic systems, these usually complicated time series are almost stochastic, and hence their variation is assumed unpredictable. For this purpose, nonlinear and predictable examinations are used to test the existence of determined chaotic trend and nonlinear process in daily time series of Tehran’s stock index from 1387/4/8 to 1392/7/10.The results reflect that sign test proves the non-stochastic nature of price index. The BDS’ results and those of sign test show that stock price index follows a nonlinear process. The independence tests like BDS test, White test, Chow test, test the correlation between observations in which the results are affirmative. Moreover, the cointegration-adjusted tests are used for testing the chaotic process of the price index and the results of both are affirmative. For predicting the stock price index in ongoing periods, we have used ARFIMA, FIGARCH, LSTAR,and ESTAR. Among those models, which examine the existence of long run memory in stock price index, FIGARCH, which tests the long run memory and variance, has the most capacity of accurate prediction. Among the nonlinear models, ESTAR has the most capacity. At the last, prediction is reported for ten periods with the one head process. Manuscript profile -
Open Access Article
433 - Predictability Test of Stock Market Price Index in Iran Investment Market and comparing Linear and Nonlinear models predictability potentials
Karim Emami Ghodratollah EmamverdiSince the highly complicated Time Series such as Stock Market Prices are usually stochastic, their changes are assumed to be unpredictable. Some tests which have been used to study the statistical observations related to the economical variables e.g. Stock Market Price, MoreSince the highly complicated Time Series such as Stock Market Prices are usually stochastic, their changes are assumed to be unpredictable. Some tests which have been used to study the statistical observations related to the economical variables e.g. Stock Market Price, are often go wrong while encountering the chaotic data and recognize them as stochastic ones, though these data are actually generated from the deterministic systems which bear few tribulations. For this reason the predictable and non-linear tests such as HURST, BDS, Runs Test, and Correlation Dimension have been used to study the existence of deterministic chaotic trend and non-linear process in Time Series of Daily Stock Market Price Index of TEHRAN STOCK EXCHANGE from 23 rd October, 2000 to 24 th September, 2002. The result of the above mentioned tests shows the predictability and the existence of a non-linear process in the sample data. After the illustration of predictability and the non-linear process in daily stock index data, then the linear time series models (AR), non-linear (GARCH) and Artificial Neural Network (ANN) have been estimated to present a suitable model for predicting the Stock Price Index. Comparing the potential of predictability of these models by such criteria as: CDC, RMSE, MAE, MAPE and U-THEIL inequality coefficient, it has been revealed that there is the highest potential of predictability in Artificial Neural Network models than the other ones Manuscript profile -
Open Access Article
434 - بررسی مقایسهای اثر تورم بر تقاضای بیمههای عمر در کشورهای در حال توسعه
ابراهیم عباسی علیرضا دقیقی اصل سکینه حسین خانی -
Open Access Article
435 - A Projection of Energy Consumption in Iranian Agriculture Sector
ابراهیم عباسیAbstract Agriculture productions are dependent to fossil fuels and other energy resources. Any damage in providing energy in agriculture sector has significant effect on its output productivity. Statisticsshow that the total amount of energy consumption in the agricult MoreAbstract Agriculture productions are dependent to fossil fuels and other energy resources. Any damage in providing energy in agriculture sector has significant effect on its output productivity. Statisticsshow that the total amount of energy consumption in the agriculture sectorduring 1370-1388 has increased from 1.33 million barrels of crude oil to 4.43 (equivalent to 1.3 times higher). Petroleum products are the main sources of energy consumed in this sector. Inthis paper, in order to forecast the energy consumption, value added of agriculture sector by anARIMA model has been calculated. Then based on the average energy intensity in existing situation (7.0) andfuture years we forecasted three scenarios for energy consumption (Onefavorable and two unfavorable scenarios) up to 1410. High-energy intensity will create social costs and damages to environmental via emission of greenhouse gases. Subsidy payment to energy consumption has led to vulnerability to environmental problem .Inorder to optimize the energy consumption and reduce its intensity in theagricultural sector different strategies should be considered such as decreased in the use of fossilenergy and using new energies. Manuscript profile -
Open Access Article
436 - پیشبینی قیمت بنزین فوب خلیجفارس با استفاده از مدلهای ARIMA و ARFIMA
حمید آماده فرشید عفتی باران امین امینی -
Open Access Article
437 - The introduction of the international exchange market (FOREX) and identify factors that predict the real exchange rate in Iran
مرجان Daman keshideh نازی Mohamadzadeh aslFOREX is one of the most important and largest financial markets in the world. This market primarily used to reduce the risk of exchange rate changes and the second place as a way to profit the difference in rates. This article has two main approaches: First to introduc MoreFOREX is one of the most important and largest financial markets in the world. This market primarily used to reduce the risk of exchange rate changes and the second place as a way to profit the difference in rates. This article has two main approaches: First to introduce and review how activity in the FOREX market, the second, most important preconditions for the presence in this market forecast exchange rate changes, the factors affecting the real exchange rate in using the ARDL method is studied. The survey results show that the variables government spending, oil revenues, capital flows and the degree of openness of the economy, including the main factors influencing the real exchange rate in Iran. Manuscript profile -
Open Access Article
438 - پیشبینی نقدینگی بر اساس برآورد نقطهای و بازهای روش آریما و مقایسه آن با روش هموارسازی نمایی دوگانه
جعفر احمدی شالی مهدی وصفی -
Open Access Article
439 - طراحی الگویی مناسب مدیریت نقدینگی و پیش بینی ریسک آن در بانک صادرات ایران
علی اسماعیل زاده حلیمه جوانمردی -
Open Access Article
440 - پیشبینی تلاطم بازدهی سکه طلا در بازار داراییهای مالی ) رهیافت ANN-GARCH)
فرزین اربابی -
Open Access Article
441 - Modeling and Estimating the return of Tehran Stock Exchange using dynamic models
Zhila Rostami Shahram Fattahi Kiomars SohailiAbstractSince the creation of the stock market in the nineteenth century, many researchers have focused on research into stock price forecasting models and market returns. Statistical prediction models such as Arma, Arima, Arch, have been widely used but none of them ha MoreAbstractSince the creation of the stock market in the nineteenth century, many researchers have focused on research into stock price forecasting models and market returns. Statistical prediction models such as Arma, Arima, Arch, have been widely used but none of them have had the desired result. Therefore, many researchers have recently considered the stock market as a nonlinear dynamic system. The application of nonlinear models as well as advanced techniques, although not many years have begun, but in a short time has been able to open its place in various sciences. The purpose of this study is to predict the stock index using the dynamic model averaging DMA and also the method of the dynamic model selective DMS and the use of quarterly data for the years 1380-1399. The main advantage of the model used in the present study is the introduction of a large number of independent variables for its dynamics without the usual problem of overfitting appearing in the model. In this paper, the effect of some macroeconomic variables on the process of modeling and forecasting stock returns on the stock exchange was investigated. The results of the article showed that the probability of entering the variables of money supply growth, quasi-money growth, inflation, land price index growth in large cities is more than other input variables. Manuscript profile -
Open Access Article
442 - پیشبینی قیمت جهانی گندم و صرفهجویی ارزی در ایران
شهریار نصابیان شهاب الدین قشقایی -
Open Access Article
443 - Fuzzy intelligent forecasting approaches and tools in the field of digital currencies: A systematic review
Davood ZareKhaneghah Ali Mohammadi Mohammad Imani Barandagh Amir NajafiAbstract Digital currency, is one of the most important factors in the success of organizations that will be present in the arena of global competition. In the present review, the most important theories of digital currency forecasting based on fuzzy hybrid models and MoreAbstract Digital currency, is one of the most important factors in the success of organizations that will be present in the arena of global competition. In the present review, the most important theories of digital currency forecasting based on fuzzy hybrid models and artificial neural networks have been systematically investigated. These models mainly focus on supervised methods for measuring hybrid models. Also, basic concepts about the history of hybrid models from the first proposed models to current developed models, their combinations and architectural capabilities, data processing and measurement methods of these intelligent models are presented so that evolution This category of intelligent systems is analyzed. Finally, the features of prominent (leading) models and their applications in digital currency forecasting are presented. The results show that fuzzy neural network models and their derivatives are efficient in predicting digital currency with very high accuracy and with good justification capability that is used in a wide range of economic and scientific fields. Manuscript profile -
Open Access Article
444 - International Studies in Perspective of Positivism and Post- Positivism Traditions in International Relations
Hassan EyvazzadehAbstract: The study of international relations fall into two epistemological traditions: Positivism and post-positivism. The main question is what is the purpose of research and study of international relations? This article argue that the Purpose affected by research MoreAbstract: The study of international relations fall into two epistemological traditions: Positivism and post-positivism. The main question is what is the purpose of research and study of international relations? This article argue that the Purpose affected by researcher epistemological Position. In the study of international relations if researcher stay put in framework of positivism epistemology, thus, your purpose of the study will be containment and prediction of international relations phenomena. But, if she/ he stay put in the post positivism epistemology the Purpose will be understanding and emancipation of phenomena. The logic of this article is dialectic logic. Manuscript profile -
Open Access Article
445 - Investigating the Impact of Business Unit Lifetime (Company Age) in Multidimensional Analysis Method for Predicting Legal Credit Risk of Legal Purchase (Case Study of Commercial Banks)
Neda Razmi ali laalbar Soleyman Hasan nejadThe study of the economic system at the international level shows the fact that there is always a close relationship between investment and the level of economic development of countries. This means that countries with an efficient model in allocating capital to differe MoreThe study of the economic system at the international level shows the fact that there is always a close relationship between investment and the level of economic development of countries. This means that countries with an efficient model in allocating capital to different economic sectors, often have higher economic development and consequently social welfare. This is a study of commercial banks. This study was conducted to investigate the effect of business unit life (company age) in a multidimensional analysis method to predict the credit risk of legal customers (studied by commercial banks) and the analysis was reviewed and the desired results were presented. .In general, according to the useful results obtained from the statistical test, which indicates 85% accuracy of the multidimensional analysis model of preferences in mode A and indicates the absence of errors on average in mode B.Therefore, it can be concluded that examining the lifespan of a business unit can increase the accuracy of the above model. Manuscript profile -
Open Access Article
446 - بررسی عوامل مؤثر بر رفتاربدبینانه(منفی) مصرف کنندگان
بهرام خیری مولود سادات فرازنده مهر حامد رضی پور -
Open Access Article
447 - تاثیر مدیریت سود فزاینده و مدیریت سود کاهنده بر کیفیت گزارشگری مالی
یداله تاری وردی عباس نعیمی مریم رستمی -
Open Access Article
448 - سودمندی رگرسیونهای تجمیعی و روشهای انتخاب متغیرهای پیشبین بهینه در پیشبینی بازده سهام
محمد حسین ستایش مصطفی کاظم نژاد -
Open Access Article
449 - تأثیر خطای پیشبینی سود مدیریت بر پایداری اجزای نقدی و تعهدی سود و ارزشیابی بیش از حد سهام
محمدرضا نیکبخت علی قاسمی محمد ایمانی برندق -
Open Access Article
450 - تاثیر تخصص مالی اعضای کمیته حسابرسی بر ویژگیهای سود پیشبینی شده
رضا جامعی آزاده رستمیان -
Open Access Article
451 - The impact of stock option pricing model and the quality of earnings and profits
جواد Moradi زهرا TahmoresIn this study, we examine the relation between earnings quality and earnings pattern and pricing of listed companies in Tehran Stock Exchange (TSE). We try to find the answer for this question "is there any direct and positive relation between earnings pattern and prici MoreIn this study, we examine the relation between earnings quality and earnings pattern and pricing of listed companies in Tehran Stock Exchange (TSE). We try to find the answer for this question "is there any direct and positive relation between earnings pattern and pricing?”. Earnings patterns which are used are "increasing annual earnings, meeting or exceeding management forecasts and smoothing". The numbers of statistic community are 430 companies in TSE. We 98 companies these statistic communities during 1379 – 1386 by restricting the companies that meet some crotieria for doing the research. We use the information Financial Statements, Rahavard Novin, Tadbir Pardaz and libraries archives. For testing the Hypothesises, Pearson coefficient of correlation and multi variable regression model are used. The results show that there is a direct and positive relation between earnings pattern (smoothing), earnings quality and pricing, while there is no relation between earnings pattern (increasing annual earnings and meet or exceed management forecasts) and earnings quality. Also, in this study we try to find patterns, effective for valuation of share prices. The results of testing the first hypothesis show that there is a positive and direct relation between earnings pattern (smoothing) and pricings and the second hypothesis confirms that the relation between other earnings patterns and earnings quality is negative and indirect. Our final analysis examines whether the pricing effects associated with earnings patterns are a function of the quality of earnings. The results show that earnings quality level has no effect on the relationship between earnings patterns and stock prices. Manuscript profile -
Open Access Article
452 - Barriers in determining the stock price by ANN
رویا Darabi ربابه KarimiThe Extant Preventives in Determining Price of Shaves by Using Artificial Neural Network(In Metal and Mineral Industries) Roya Darabi Robabeh Karimi Raste Kenari (Received: 10/Apr/2014; Accepted: 12/Jun/2014) Abstract This study aims to investigate the extant preventive MoreThe Extant Preventives in Determining Price of Shaves by Using Artificial Neural Network(In Metal and Mineral Industries) Roya Darabi Robabeh Karimi Raste Kenari (Received: 10/Apr/2014; Accepted: 12/Jun/2014) Abstract This study aims to investigate the extant preventives in determining price of shaves by using artificial nerve network in metal and mineral industries companies accepted in Tehran Securities Exchange. We applied two statistical analysis and nerve network methods for examination of hypnotizes. A questionnaire was created for statistical analysis method and statistical society including senior experts of securities exchange course and instructors Tehran Azad University, who are familiar with the concepts of nerve network and also forecasting shares prices. The research hypnotizes were dealt with use of t test and score, ultimately all hypnotizes were approved. In the nerve network, the assumptions of research were studied by the use of nerve network and after the distribution of the error and Market-Loren berg educational model and it was determined that while all the indexes were entered into the network as input, the for forecasts of prices do not enter into the network as precisely as the indexes do enter. Also, the rate of network error was increasing. The results of nerve network corresponded with the results of statistical analysis. In other words, in both methods, the indexes have been marked as obstacles for forecasting the shares prices by the use of nerve network method. Key Words: Nerve Network, Forecast of Shares Price, Relative Strength Index, Rate of Shares Cost Index, After Distribution of Error. Manuscript profile -
Open Access Article
453 - The Comparison of Financial Crisis Prediction Strength of Different Artificial Intelligence Techniques
Zahra Pourzamani Hassan kalantariRapid technological advances and vast environmental changes, leading to increasing competition and limit access to benefits and likely to suffer financial crisis has increased. Purpose of this study is investigating financial crisis prediction strength of different arti MoreRapid technological advances and vast environmental changes, leading to increasing competition and limit access to benefits and likely to suffer financial crisis has increased. Purpose of this study is investigating financial crisis prediction strength of different artificial intelligence techniques(linear and nonlinear genetic algorithm and neural network). Based on available information and statistics, of all companies listed in Tehran Stock Exchange, 72 companies have been subject to Article 141 trade law and 72 companies have not been subject to this Article was elected. Results of Mc-Nemar test for genetic algorithms techniques and neural network showed that there are not significant differences between linear and nonlinear genetic algorithms with neural network. Although the predictive accuracy of nonlinear genetic algorithm(90%) and linear genetic algorithms(80%) is more than of the neural network(70%) but this difference is not statistically significant. Manuscript profile -
Open Access Article
454 - بررسی رابطه بین الگوهای پیش بینی بحران مالی (الگوهای مورد مطالعه: آلتمن و دیکین)
هاشم نیکو مرام زهرا پورزمانی -
Open Access Article
455 - Bonding costs related to the quality of earnings and forecast error
علی Esmaeilzadeh علی MAERNOOSHThe Relation of Cost Sticky with Earning Forecast and Earning Quality Ali Esmaeil Zade Ali Mehrnoush (Received: 23/Dec/2013; Accepted: 22/Feb/2014) Abstract One of the basic assumptions that reflect management accounting change related costs associated with increased an MoreThe Relation of Cost Sticky with Earning Forecast and Earning Quality Ali Esmaeil Zade Ali Mehrnoush (Received: 23/Dec/2013; Accepted: 22/Feb/2014) Abstract One of the basic assumptions that reflect management accounting change related costs associated with increased and decreased activity level. But recently, with the assumption of bond issue costs, by Anderson and And his colleagues have discussed, in the sense that the increase in costs by increasing the activity level Most of the reduction in costs in exchange for the reduction in activity. The main objective of this study is that adherence cost studied in the Tehran Stock Exchange, and administrative expenses, selling, general and Total costs and cost of goods sold as samples were analyzed. Based on the results of listed companies in Tehran Stock Exchange for a period of 6 years the year 1384's to 1390, shows the increment in cost stickiness general, and administrative and selling expenses, general and Cost of goods sold decreased earnings forecast errors and Earnings Qulity. The results for the 84 firms in various stock is presented. Key Words: Cost Stickiness, Earning Forecast, Earning Quality, Related Costs. Manuscript profile -
Open Access Article
456 - اهمیت کیفیت محیط اطلاعات داخلی در اجتناب مالیاتی
غلامرضا کرمی امیر فیروزنیا حمید کلهرنیا -
Open Access Article
457 - The Effect of Management Forecast Quality on Investment Efficiency Considering the Role of Ownership Structure
فاطمه دهقان امید پورحیدری احمد خدامی پورAbstract The purpose of this paper was to investigate the Effect of Management Forecast Quality on investment efficiency considering the Moderating role of ownership structure. The statistical population of the research is listed companies in Tehran Stock Exchange. In MoreAbstract The purpose of this paper was to investigate the Effect of Management Forecast Quality on investment efficiency considering the Moderating role of ownership structure. The statistical population of the research is listed companies in Tehran Stock Exchange. In this regard, the data of 129 companies in the period between 2009 to 2018, has been investigated by applying a multivariate regression model. Data has been extracted from Codal site and Rahaward software Version 3. The data were analyzed by eviews software version 11. Before testing the research models, using F-Limer and Hausman tests, panel data with fixed effects were selected for testing the models. The present study is of a correlational nature and in terms of purpose, it is an applied research. In this study, institutional ownership and ownership concentration were used to measure ownership structure. The results indicated that earnings Forecast accuracy has a positive and significant effect on investment Efficiency. In addition, institutional ownership does not strengthen the relationship between earnings Forecast accuracy and investment efficiency. But the ownership concentration moderates the effect of earnings Forecast accuracy on investment efficiency. Manuscript profile -
Open Access Article
458 - Reliable earnings forecasts feasibility report mentioned capital increase
رویا Darabi مهناز Rabiei مهران FarhanghThe aim of this study is to assess the errors which would occur in the prediction of absolute earnings in the increasing capital reporting. To achieve mentioned objective, we have examined some information as performance evaluation measures including assets, debits, sal MoreThe aim of this study is to assess the errors which would occur in the prediction of absolute earnings in the increasing capital reporting. To achieve mentioned objective, we have examined some information as performance evaluation measures including assets, debits, sales, financial leverage ratio, internal rate of returns and the errors which would occur in the prediction of absolute earnings in the increasing capital reporting 1386 to 1388. The correlation analysis with linear regression and test variance analysis have been used as the statistical method and the gathered data has been analyzed via the SPSS software. On top pf that, rationality of the regression equation and its coefficients were investigated respectively with F and T tests. The results reveal a significant relation between the errors which would occur in the prediction of absolute earnings in the increasing capital reporting and financial position of the companies, internal rate of returns, the industry type, the reports type (financing for working capital or financing for development plans). In addition the errors which would occur in the prediction of absolute earnings was found independent to financial leverage rate, when the companies get into the Stock Exchange and size of the companies. Manuscript profile -
Open Access Article
459 - The Relationship of Conditional and Unconditional Conservatism with Earning Anticipation amount
Mohammad Hossein Setayesh Hamid Reza RezaeiThe main purpose of this paper is review of the relationship between conservatism and amount of earning anticipation of companies accepted in Tehran stock exchange. For quantifying the conditional conservatism, we use two measures including negative coefficient of total MoreThe main purpose of this paper is review of the relationship between conservatism and amount of earning anticipation of companies accepted in Tehran stock exchange. For quantifying the conditional conservatism, we use two measures including negative coefficient of total voluntary(non-operational) accrual items to total assets and the proportion of net income before unexpected items to market value of stockholders equity. Likewise, for quantifying the unconditional conservatism, we use two measures namely the rate of book value to market value of net assets and negative coefficient of total accrual items total assets average. Research hypothesis studied on each industries level and total industry level. The findings imply that there was no significant relationship between including negative coefficient of total voluntary(non-operational) accrual items and anticipated earning in total industry level.Also, there was a significant relationship between the proportion of net income before unexpected items to market value of stockholders equity and anticipated earning in plant and equipment, electric and ceramic tile industries; but there was not a significant relationship between them in total industry level. In addition, there was an insignificant relationship betweenthe proportionof book value to market value of net assets andanticipated earning in electric and food-beverage industries and this hypothesis corroborated in other industries and total industry level. Eventually, the results represent that the negative coefficient of total accrual items to total assets average had an insignificant relationship on anticipated earning. Manuscript profile -
Open Access Article
460 - The relationship between earnings quality and performance features
فروغ Rostamiyan محمد KHodaei مجتبی HedarThe conflict of interest between issuers of financial statements and the users of financial statements have been the subject of significant debate for using different methods of accounting accepted principles and implementing earning as an important criterion for decisi MoreThe conflict of interest between issuers of financial statements and the users of financial statements have been the subject of significant debate for using different methods of accounting accepted principles and implementing earning as an important criterion for decision making process. Thus, this controversial results, made us to contribute to this debate by investigating the relationship between earnings quality attributes and performance of Iranian public listed firms in Tehran stock exchange. We examined sample of 63 firms that randomly ed in the period 2002 to 2009. We derived a summary measure of earnings quality by applying factor analysis on two variables representing different components of two primary dimensions of earnings quality: Feedback value (FV) and Predictive Value (PV). Also two common financial performance measures namely Returns on Assets (ROA) and Tobin's Q were examined. We then provide empirical evidence to address the question, whether earnings quality of Iranian listed firms is associated with their performance or not. Based on using pool regression, we interpret our results that, the feedback value of earnings has both positive and significant association with firm performance measures. On the other hand, predictive value has both negative and significant association with returns on assets and has not significant association with Tobin's Q. further, the current study provide novel evidence towards the understanding of more powerful association between feedback value with firm performance measures than predictive value. Specifically in this survey, we controlled the influence of essential firm characteristics namely size, leverage, and growth on firm performance. Manuscript profile -
Open Access Article
461 - Investigating the relationship between Integrated Report Quality and earnings forecasting bias and Share Price Informativeness
Muhammad Vahdani Javad Muhammadi MehrAbstract Integrated financial reporting provides investors with a comprehensive understanding and insight into the company and reduces the costs of obtaining information, processing, facilitating and combining relevant and effective information, and ultimately raising MoreAbstract Integrated financial reporting provides investors with a comprehensive understanding and insight into the company and reduces the costs of obtaining information, processing, facilitating and combining relevant and effective information, and ultimately raising stock price awareness, improving information quality and facilitating more efficient capital allocation. The purpose of this study is to investigate the relationship between integrated financial reporting with earnings forecasting bias and stock price awareness. The statistical population of this research is all companies listed on the Tehran Stock Exchange and 167 companies in the period 1391 to 1399 have been selected by systematic elimination method. Also, to test the research hypotheses, a multivariate regression model based on composite data was used. The results of the first hypothesis indicate that there is a direct and significant relationship between integrated financial reporting and behavioral financial bias in stock price forecasting. The results of testing the second hypothesis showed that there is a direct and significant relationship between integrated financial reporting and accuracy of profit forecasting. Integrated financial reporting with disclosure of financial and non-financial information from the financial reporting process and corporate activity makes investors and analysts more accurate forecasts. The results of testing the third hypothesis showed that there is a direct and significant relationship between integrated financial reporting and stock price awareness. He said that by combining financial and non-financial information, the process of creating value for the company in the form of financial reporting makes the information content of stock prices informative and investors in stocks make optimal decisions according to rational investment theory. Manuscript profile -
Open Access Article
462 - مقایسه قدرت داده های حسابداری نقدی و تعهدی در پیش بینی جریان های نقدی آتی با استفاده از اطلاعات مالی میان دوره ای شرکت های پذیرفته شده در بورس اوراق بهادار تهران
رویا دارابی شکوفه اعتبار -
Open Access Article
463 - بررسی کارایی شاخص های کلان اقتصادی در الگوهای پیش بینی بحران مالی در محیط اقتصادی ایران (الگوهای مورد مطالعه : تافلرو دیکن
زهرا پورزمانی آزیتا جهانشاد وجیهه رحمتی -
Open Access Article
464 - Integration of artificial intelligence techniques to Model to predict stock prices
مهدی Moradzadeh رویا Darabi رامین ShahalizadehStock exchange is a secure way to gain public trust for investment in different securities with varying risks. In this way small and scattered capitals which cannot be utilized alone can be accumulated and a huge investment can be made of them for economic development a MoreStock exchange is a secure way to gain public trust for investment in different securities with varying risks. In this way small and scattered capitals which cannot be utilized alone can be accumulated and a huge investment can be made of them for economic development and progress. In stock exchange, there are a lot of sensitivities to price formation course. This has caused that changes related to such phenomenon to be systematically analyzed. In recent years, a variety of models have been employed by specialists for prediction of share price. Since Artificial Intelligence Techniques which include Neural Networks, Genetic Algorithm and Fuzzy Logic have achieved successful results in complex problems, they are used more for this purpose. Present study intends to answer the question whether using a combination of Artificial Intelligence Technique, a model can be set up which compared to other linear and non-linear methods predicts share price with less error. In this research, to predict stock price (Tehran stock exchange - Iran Khodro CO), a combination of Artificial Intelligence Methods including Neural Networks, Fuzzy Logic and Genetic Algorithm are used and this combined model is compared with Neural Network Methods, the title for one of the other Artificial Intelligence Models, and ARIMA linear model, given R2, MAE, MAPE, MSE. The results of this research shows that the superiority of Hybrid model compared to other models are examined. Manuscript profile -
Open Access Article
465 - پیش بینی وضعیت مالی و اقتصادی شرکت ها با استفاده از نسبت های مالی مبتنی بر سودآوری، جریان های نقدی و رشد
زهرا پورزمانی آزیتا جهانشاد شهرام عین قلایی -
Open Access Article
466 - Providing Three-Dimensional Composite Model (Financial, Economic, Sustainability) in predicting Companies' Financial Distress
احمد برگ بید علی جعفری hasan salehnejadFinancial distress is a serious issue for the economic life of countries and forecasting distress for various groups including managers, banks, investors, policymakers and auditors is of great importance. The purpose of this study is to provide a combined three-dimensio MoreFinancial distress is a serious issue for the economic life of countries and forecasting distress for various groups including managers, banks, investors, policymakers and auditors is of great importance. The purpose of this study is to provide a combined three-dimensional model (financial, economic, sustainability), two-dimensional model (financial and economic) and one-dimensional (financial) in predicting financial distress of companies and also comparing the predictive power of models with component analysis approach. It is the principle that using the post-event approach (through past information) is of the descriptive-correlation type and based on the objectives is also of the applied research type. Also, the statistical population and spatial scope of this research, listed companies and its time domain. Using the systematic removal method, 113 listed companies were selected as a sample. The results showed that the three-dimensional hybrid model (financial, economic, sustainability) has a high predictive power for helplessness. Manuscript profile -
Open Access Article
467 - تفاوتهای فردی و قضاوت حرفه ای حسابرس
مسلم سعیدی گراغانی احمد ناصری -
Open Access Article
468 - Compare the performance of internal and comparative data analysis, genetic algorithm nonlinear techniques to forecast profitability
زهرا PurzamaniAlthough knowledge about how users of financial statements make decisions is limited, it certainly can be said that a part of decision-making relates to predictability of future profitability. Also, profitability is used as a basis for assessing the efficiency of corpor MoreAlthough knowledge about how users of financial statements make decisions is limited, it certainly can be said that a part of decision-making relates to predictability of future profitability. Also, profitability is used as a basis for assessing the efficiency of corporate managers. This study, with the aim of introducing an appropriate algorithm for predicting the profitability to the decision makers, by the top 24 financial ratios as independent variables, compares the abilities of internal and comparative data analysis in Non-Linear Genetic Algorithm in anticipating the future profitability of companies listed in Tehran Stock Exchange during the years 2002 to 2012. Results of tests indicated that prediction accuracy of internal data analysis in Non-Linear Genetic Algorithm (90.04%) was greater than that of comparative data analysis in Non-Linear Genetic Algorithm (72.85%). Manuscript profile -
Open Access Article
469 - Alanshdh and predicted earnings per share content in explaining abnormal returns
مهدی Salehi S.M Mosavi shiri محمد EbrahimiThe Information Content of Declared Dividends Per Share and Predicted Earnings Per Share in Explaining Abnormal Stock Return Mahdi Salehi Mahmoud Mousavi Shiri Mohammad Ebrahimi Swizi (Received: 29/Dec/2013; Accepted: 01/Mar/2014) Abstract The aim ofthisstudy is to inve MoreThe Information Content of Declared Dividends Per Share and Predicted Earnings Per Share in Explaining Abnormal Stock Return Mahdi Salehi Mahmoud Mousavi Shiri Mohammad Ebrahimi Swizi (Received: 29/Dec/2013; Accepted: 01/Mar/2014) Abstract The aim ofthisstudy is to investigatethe information content ofdeclared dividends per shareand predicted earnings per share in explainingabnormalstockreturn. For this aim we used measures of unexpected profitand adjusted earning prediction that demonstrator earning per share and earnings per share prediction. The research population is Tehran Stock Exchange and the sample is 50 listed companies that ed by elimination and cover financial information during 2008 – 2011. The results show that the correlation between declared dividendsper shareandpredicted earnings per sharewithabnormalstockreturn is positive and important. Other results show that information content of declared dividendsper share is more than of predicted earnings per share. Key Words: Declared Dividends Per Share, Predicted Earnings Per Share, Abnormal Stock Return Manuscript profile -
Open Access Article
470 - The Relationship between the Product Market Competition and Information Asymmetry; Structural Equation Modeling Approach
اکبر کنعانی رضوان حجازی مهرداد قنبری بابک جمشیدی نویدSince competition in the product market is one of the factors influencing the decisions of managers and investors, it is therefore considered as an important component in the reduction of information asymmetry in terms of insiders and outsiders decision making.The purpo MoreSince competition in the product market is one of the factors influencing the decisions of managers and investors, it is therefore considered as an important component in the reduction of information asymmetry in terms of insiders and outsiders decision making.The purpose of this study was to investigate the effect of competition in product market on information asymmetry.The statistical population of this research is the companies accepted in the TSE by using structural equation modeling approach. In order to measure the level of competition, the Herfindahl-Hirschman index and to measure the information asymmetry, Bid-Ask criteria and firm size, earning forecast error and growth opportunities was used. After assuring the ability to measure the information asymmetry variable by the indicated indicators as well as the appropriate fit for the measurement and structural model of the research, the results indicate that the level of competition in the product market has a significant effect on the information asymmetry. In other words, with increasing competition in the product market, information asymmetry decreases. Manuscript profile -
Open Access Article
471 - تأثیر جریانهای نقدی آزاد مازاد، نظام راهبری شرکتی و اندازه شرکت بر پیش بینی پذیری سود
ناصر ایزدی نیا وحید رو ح الهی -
Open Access Article
472 - The impact on the accuracy of earnings management to predict future operating cash flows
یداله Tari verdi مهدی Moradzadeh fard مریم ROSTAMIThe Effect of Earnings Management on the Accuracy of Predicting Future Operating Cash Flows Yadollah Tariverdi Mehdi Moradzadeh Fard Maryam Rostami (Received: 02/Jun/2014; Accepted: 05/Mar/2014) Abstract In this study the effect of earnings management on the accuracy of MoreThe Effect of Earnings Management on the Accuracy of Predicting Future Operating Cash Flows Yadollah Tariverdi Mehdi Moradzadeh Fard Maryam Rostami (Received: 02/Jun/2014; Accepted: 05/Mar/2014) Abstract In this study the effect of earnings management on the accuracy of predicting future operating cash flows has examined. For measuring accruals, we have used cash flows approach. Kasznik model has been usedfor estimating earnings management. Also, adjusted Barth modelhas been employed for measuring the accuracy of predicting future operating cash flows by components of operating earnings. The hypothesis of current research is tested by panel data, using information of 70 companies in the Tehran Stock Exchange. Our findings show that earnings management by accruals decreases the accuracy of predicting future operating cash flows, that is managers distort financial reporting and they do earnings management opportunistically to benefit themselves. Key Words: Earnings Management, Opportunistic Earnings Management, Kasznik Model, The Accuracy of Predicting Future Operating Cash Flows, Adjusted Barth Model. Manuscript profile -
Open Access Article
473 - The impact on the quality of earnings bankruptcy prediction using artificial neural network
بیتا Mashikhi H.R GanjiThe Effect of Earnings Quality on Predicting Bankruptcy by Using Artificial Neural Networks Bita Mashayekhi Hamidreza Ganji (Received: 16/Apr/2014; Accepted: 19/Jun/2014) Abstract Predicting of entities’ going- concern assumption in the future periods is an import MoreThe Effect of Earnings Quality on Predicting Bankruptcy by Using Artificial Neural Networks Bita Mashayekhi Hamidreza Ganji (Received: 16/Apr/2014; Accepted: 19/Jun/2014) Abstract Predicting of entities’ going- concern assumption in the future periods is an important element in decision-making process of many investors. So, ing the predictor variables have been discussed as a challenging issue in the literature of bankruptcy prediction that accounting earnings & profitability variables have been at the top of these issues. Therefore earnings quality has been one of the important measures in the decision-making process of investors in field of bankruptcy prediction. This study has attempted to compare the prediction power of profitability variables among high quality and low quality earnings of Tehran Stock Exchange(TSE) companies and examine the effect of earnings quality on the efficiency of profitability variables in predicting the bankruptcy. In a sample of TSE companies, using artificial neural networks we find that the predictive accuracy of artificial neural networks for high quality earnings companies is significantly greater than of firms low quality earnings. Key Words: Profitability, Predictability, Earning Quality, Bankruptcy, Artificial Neural Network. Manuscript profile -
Open Access Article
474 - پیشبینی ورشکستگی شرکتها مبتنی بر سیستمهای هوشمند ترکیبی
مهدی غضنفری اقبال رحیمی کیا علی عسکری -
Open Access Article
475 - تأثیر تفکیک اقلام تعهدی در قدرت پیشبینی آنها درباره جریانات نقد آتی
مرتضی خیری فرزانه حیدر پور -
Open Access Article
476 - تأثیر متغیرهای کلان اقتصادی بر سود آتی حسابداری
سید عباس هاشمی هادی امیری زهرا تیموری -
Open Access Article
477 - Relationship between Management Profit Forecasting Error and Adjustment of Profit Forecast with Corporate Accruals
Alireza Rahimi Aref Foroughi Majid AzadiAbstractNet profit and its adjustments are among the most valuable information used by investors. This study seeks to answer the question whether company conditions (ambiguity or inability to understand economic information) affect the relationship between forecasting e MoreAbstractNet profit and its adjustments are among the most valuable information used by investors. This study seeks to answer the question whether company conditions (ambiguity or inability to understand economic information) affect the relationship between forecasting error and adjustment of profit forecasting by management or not? For this purpose, first, the relationship between accruals (abnormal) and error and adjustment of profit forecast, test and then the effect of ambiguity and inability to understand economic information on the above relationship is examined. The research sample includes 91 companies listed on the Tehran Stock Exchange. Findings indicate that there is a positive and significant relationship between working capital accruals and abnormal working capital accruals with management forecast error, but there is a negative relationship between working capital accruals and abnormal working capital accruals wThere is significance. Also, conditions of ambiguity did not affect this relationship, but the inability to understand economic information strengthens this relationship.ith negative forecast and adjustment. Manuscript profile -
Open Access Article
478 - ویژگیهای رفتاری مدیران و نقدشوندگی سهام
رحمت اله آزاد یحیی کامیابی مهدی خلیل پور -
Open Access Article
479 - رابطه بدبینی مدیریت با کفایت وجه نقدو دفعات پوشش هزینه بهره با توجه به میزان سود انباشته شرکتها
قربانعلی اسماعیل زاده سید علی نبوی چاشمی -
Open Access Article
480 - تأثیر عدم تقارن اطلاعاتی، عدم نقدشوندگی سهام و تمرکز مالکیت بر دقت پیشبینی سود
علی ذوالفقاری مهدی مرادی مهدی بهنامه زکیه مرندی -
Open Access Article
481 - نقش بازده مبتنی بر سبک در پیشبینی بازده آتی
لیلا صفدریان داریوش فروغی فرزاد کریمی -
Open Access Article
482 - اثر تعدیل کنندگی راهبری شرکتی بر ارتباط بین رقابت در بازار محصول و کیفیت سود پیش بینی شده توسط مدیریت
حسین فخاری محسن حسن نتاج کردی -
Open Access Article
483 - Usefulness Offair Value of Loan Facility for Predicting Banks, Future Operational Cash Flows
مریم رستمی حمیدرضا کردلویی غلامحسن تقی نتاج ملکشاه فرهاد حنیفیIn this study, the model of barth et.al (2001) was applied for predicting banks, future operational cash flows and for calculating fair value of loans was applied the model of Tschirhart et al. (2007).The hypotheses of the study were tested through the panel data gather MoreIn this study, the model of barth et.al (2001) was applied for predicting banks, future operational cash flows and for calculating fair value of loans was applied the model of Tschirhart et al. (2007).The hypotheses of the study were tested through the panel data gathered from 18 listed banks in Tehran Stock Exchange. In this researchoperational cash flows of one and two future-year of banks are considered. The findings of the first hypothesis of the research indicated that with 90% assurance only changes of fair value has a significant and negative relation with one year-future operational cash flows and changes of cost of loans has no effect. The findings of the second hypothesis of the research indicated that with 90% assurance both changes of fair value and changes of cost of loanshave a significant and negative relation with two year-future operational cash flows. Manuscript profile -
Open Access Article
484 - The Effect of Accounting Earning Growth on Macroeconomic Indicator
محسن عرب زاده ناصر ایزدی نیا سعید صمدیThe main objective of this study is to investigate the effect of firms' cumulative accounting earning growth on macroeconomic indicators such as GDP and net investment in national accounts.In other words, the effect of firms' cumulative accounting earning growth on futu MoreThe main objective of this study is to investigate the effect of firms' cumulative accounting earning growth on macroeconomic indicators such as GDP and net investment in national accounts.In other words, the effect of firms' cumulative accounting earning growth on future GDP and net future investment and also the future GDP growth forecast errors and the future growth in net investment forecast errors has been studied.This research, in terms of purpose is a kind of applied research. The method is based on correlation and regression based on actual financial statements of companies listed on the Tehran Stock Exchange and macroeconomic data such as GDP and net investment from national accounts.The statistical population of the study is all companies listed in Tehran Stock Exchange during the period 2005-2017.The results show that the firms' cumulative accounting earning has an impact on the growth of future GDP and net investment in national accounts. But the firms' cumulative accounting earning hasn’t an impact on the future GDP growth forecast errors and the future growth in net investment forecast errors. Manuscript profile -
Open Access Article
485 - بررسی تاثیر پیچیدگی و عدم اطمینان محیطی برصحت پیش بینی سود مدیریت با تاکید بر کیفیت حسابرسی به عنوان متغیر میانجی
زینب محمدیان مهدی حیدری پری چالاکی -
Open Access Article
486 - Examining the relationship between academic optimism and growthProfessionalism of elementary school teachers in Chahar Borj city
Akbar MemarbashiThe purpose of this research was to investigate the relationship between academic optimism and professional growth of elementary school teachers in Chaharborj city. This research was applied research and was done with a descriptive method. The research community include MoreThe purpose of this research was to investigate the relationship between academic optimism and professional growth of elementary school teachers in Chaharborj city. This research was applied research and was done with a descriptive method. The research community included all primary school teachers of Chaharborj city, numbering 284 people (110 women and 174 men). The sample was randomly stratified using Cochran's formula in the number of 163 people (64 women and 99 men). The data collection method was library and field. In order to collect information, in the first part, the academic optimism questionnaire made by Schenen Moran et al. (2013) and has 37 items was used to measure the academic optimism of teachers. In the second part, the 18-question standard questionnaire of teachers' professional development was used. Its validity and reliability (using Cronbach's alpha 76-80%) was confirmed by its designer. Descriptive statistics were used to calculate the average and draw tables. To test the hypotheses, parametric inferential statistics (due to the normality of data distribution) and Pearson's correlation coefficient were usedAfter testing the hypotheses and analyzing the findings, the results showed that there is a relationship between academic emphasis, students' trust in their teachers, teacher efficiency and the professional development of elementary school teachers in Chaharborj city. Manuscript profile -
Open Access Article
487 - The Explanation of the Relationship between Downside Risk and Upside Risk combination in predicting Market Return Volatility
hossein rad kaftroudi mohammadhasan gholizadeh mahdi fadaeiThe volatility of financial returns plays an important role in many empirical applications, such as portfolio allocation, risk management and derivative pricing. The purpose of this research is to explain the relationship between undesirable risk and desirable risk in p MoreThe volatility of financial returns plays an important role in many empirical applications, such as portfolio allocation, risk management and derivative pricing. The purpose of this research is to explain the relationship between undesirable risk and desirable risk in predicting market return volatility. The research is descriptive in nature and applied in purpose. The statistical population of the study is the companies listed in Tehran Stock Exchange and the target sample of the companies listed in the cement industry from which the required research data can be extracted. The research period is from 1392 to 1397. This research has a theoretical model and the self-regression model was used to test the hypotheses. In the cement industry, according to the t-statistic and its coefficient of determination, it is clear that the predictor of market yield fluctuations correlates with undesirable and desirable risk. Also, the adjusted coefficient of determination is 51%, which indicates this effect. Manuscript profile -
Open Access Article
488 - Predicting Emotional Tendency of Investors Using Support Vector Machine (SVM) and Decision Tree (DT) Techniques
reza taghavi iman dadashi mohammad javad zare bahnamiri hasmidreza gholamnia roshanInvestor's emotional tendencies indicate the margin of shareholder's optimism and pessimism towards a stock. Investors' emotions, under the influence of psychological phenomena, direct people's behavior and, in many cases, make people to deviate from the rational behavi MoreInvestor's emotional tendencies indicate the margin of shareholder's optimism and pessimism towards a stock. Investors' emotions, under the influence of psychological phenomena, direct people's behavior and, in many cases, make people to deviate from the rational behavior. The purpose of this study is to use meta-innovative methods to predict the emotional tendencies of investors. In this study, using 97 financial ratios related to 176 companies listed on the Tehran Stock Exchange during the period between 2006 and 2018, investors' emotional tendencies have been predicted with the help of support vector machine (SVM) and decision tree (DT) techniques.To measure the emotional tendencies of investors, four indicators of relative strength, psychological line, trading volume and stock turnover adjustment rate have been applied. Finally, we have combined these indicators with the help of PCA method. Mean absolute error (MAE) and root mean square error (RMSE) values were used to compare predicting methods. The results of data analysis indicate that the prediction error of the support vector machine method is less than the decision tree. Manuscript profile -
Open Access Article
489 - Designing an Adjusted Return Predictive Pattern Based on Downside Risk; Evidence from the Tehran Stock Exchange
Firouz Sayadi Ali Asghar Anvary Rostamy Feridoon Rahnamay roodposhti Taghi TORABIThis paper is to develop a pattern to forecast adjusted returns according to the downside risk for the Tehran Stock Exchange. For this pursues, first, it seeks to find the factors affecting the adjusted return of companies listed on the Tehran Stock Exchange, taking int MoreThis paper is to develop a pattern to forecast adjusted returns according to the downside risk for the Tehran Stock Exchange. For this pursues, first, it seeks to find the factors affecting the adjusted return of companies listed on the Tehran Stock Exchange, taking into account the role of downside risk in the context of information asymmetry. In the second stage, it provides a pattern of forecasting adjusted returns based on downside risk. In fact, the main problem is that several internal and external effective variables affect the adjusted return according to the downside risk, and each of these variables may have positive or negative (ambiguous) effects on the adjusted return according to the downside risk. This study is to investigate the ambiguity about the role of variables affecting adjusted returns. The results of the regression model test show that the variables of capital structure, net profit, return on assets, board of directors, and duality of duties of managing director and chairman of the board at 99% confidence level and variables of dividend ratio and operating cash flow at 95% confidence level have significant effects on the adjusted return. Manuscript profile -
Open Access Article
490 - Application of econometric modeler for predicting stock prices in the capital market
Alireza Sadat Najafi Soheila SardarInvesting in the capital market requires deciding on issues such as selection, timing, price and share buybacks with market research. One of the ways to do this is to use econometric modelers. In the studies performed to compare methods or to present hybrid models, most MoreInvesting in the capital market requires deciding on issues such as selection, timing, price and share buybacks with market research. One of the ways to do this is to use econometric modelers. In the studies performed to compare methods or to present hybrid models, most econometric models have been studied without comparing and predicting the error of prediction error of other algorithms. In this research, the most efficient algorithm for solving this defect is implemented and compared with the proposed methods on selected shares and based on the proposed parameters.On the other hand, often the order of the regression and the mean of the moving average sentence are considered for the finite number of studies, which is based on Bayesian criteria for determining the p and q degrees to obtain the optimal response. This paper compares the methods of self-regressive moving average, cumulative self-regressive moving average, self-regulated seasonal moving average, self-regressive moving average with explanatory variable, cumulative mean self-regression with explanatory variable, self-regression model with variance. Generalized conditional, exponential self-regression model with generalized conditional heterogeneity variance and regression model with moving average self-regression errors for selected symbols of Tehran Stock Exchange. Manuscript profile -
Open Access Article
491 - Modeling of Gold coin futures with stochastic differential equations
Rahele Baqeri mohammadreza setayesh Reza RadfarThe capital market is one of the financial markets that in a dynamic economy can pave the way for long-term economic growth.Futures contracts that derive their values from an underlying asset, are included these financial instruments.To enter the futures market, the inv MoreThe capital market is one of the financial markets that in a dynamic economy can pave the way for long-term economic growth.Futures contracts that derive their values from an underlying asset, are included these financial instruments.To enter the futures market, the investor needs to anticipate future trends to cover his risk. For this purpose, the appropriate random differential equation has been selected to model the prediction of future coin contracts in the present study.Thus, after providing the necessary explanations about the necessity of using random models and as a result of new principles called random accounts, to introduce the most important stochastic differential equation in financial sciences including geometric Brownian, geometric Brownian with jump term, Heston and the explained model are discussed. Then, the appropriate model is selected, with a practical approach and based on the ability of each model to predict the price of futures contracts by assembling the Monte Carlo.The results of the fitness criteria regarding the predictive power indicate the superiority of the model explained in these contracts. Manuscript profile -
Open Access Article
492 - Factor Variability Test in Stock Return Forecasting Using Dynamic Model Averaging (DMA)
hosein maghsoud hamedreza vakilifard Taghi TorabiIn this study, using dynamic averaging models and monthly data in the period 2001:4 until 2018:3, Tehran Stock Exchange returns be investigated. In this regard, macroeconomics variables and parallel markets indices have been used to forecast the stock returns. Initially MoreIn this study, using dynamic averaging models and monthly data in the period 2001:4 until 2018:3, Tehran Stock Exchange returns be investigated. In this regard, macroeconomics variables and parallel markets indices have been used to forecast the stock returns. Initially, estimating various models such as Recursive models, time-varying parameter models (TVP), dynamic model selection (DMS) and dynamic model averaging (DMA) in Matlab software, It was observed that DMS model with α = β = 0.95 had higher forecast accuracy (based on MAFE, MSFE and Log (PL) metrics). Gold price (48-period), exchange rate (36-period) and inflation rate (30-period) had the highest effect on stock returns, respectively, and global oil prices and GDP had the lowest effect by 28 and 2, respectively. Finally, the results indicate that utilizing dynamic models by considering time variations in parameters and the variation of the model increases the efficiency of forecasting stock returns. Keywords: Forecasting, Stock Returns, time-varying Parameter (TVP), Dynamic Model Averaging (DMA). Manuscript profile -
Open Access Article
493 - Forecasting the Global Gold Price Movement with Marginal Distribution Modeling Approach: An Application of the Copula GARCH Gaussian and t
Mohammad reza Haddadi Younes Nademi Hamed FarhadiGiven the importance of gold prices in financial markets and the economic effects of price fluctuations, the trend of gold price changes in the national and global economy has attracted the attention of many researchers and economic analysts. Therefore, the main purpose MoreGiven the importance of gold prices in financial markets and the economic effects of price fluctuations, the trend of gold price changes in the national and global economy has attracted the attention of many researchers and economic analysts. Therefore, the main purpose of this study is to predict the trend of the global gold price movement. The purpose of this study was to introduce a combined model of the GARCH-Classic and the GARCH-Copula models and to compare them with the Garch family models in order to predict the global gold price trend in the period 01/04/2002 to 26/06/2018. The forecast horizons are 1, 5, 10, and 22 days. The prediction accuracy of these models has been evaluated and compared using RMSE error criterion. Results showed that in short-run prediction horizons, the normal Capula model with GARCH-t distribution and in long run prediction horizon, Capula- t model with the distribution of GARCH-t performs better than competing models. The hybrid model presented in this study has a high potential for predicting the trend of global gold price movement, so using this model for different sector investors, economic analysts, as well as country macro planners, can have valuable results. Manuscript profile -
Open Access Article
494 - Prediction of stock efficiency based on kernel distribution and mixture of normal distributions
Gholam reza Zeinali Narges yazdanianModeling and predicting stock returns has always been one of the challenges for researchers and investors. Hence, different methods and models have been proposed, most of which have been based on assumptions such as the distribution of returns. The kernel distribution a MoreModeling and predicting stock returns has always been one of the challenges for researchers and investors. Hence, different methods and models have been proposed, most of which have been based on assumptions such as the distribution of returns. The kernel distribution and mixture of normal distributions were examined to predict stock return in the present study. To this end, kernel functions and mixtures of normal distributions and related parameters have been estimated using maximization of likelihood function and quartiles 99%, 95% and 90% were computed for each of distributions and for 30 superior enterprises listed in Tehran Security and Exchange (TSE) at first quarter in 2019 as predictor values of stock return. In order to determine precision of prediction methods, MSE and PRED error criteria were employed and the findings showed that mixture of normal distributions and kernel approximation might propose favorable predictions for 5-day stock returns in quartiles 90% of return distribution. Comparison of precision between two methods indicated that kernel approximation, as a non parametric method for prediction of returns, leads to higher precision than mixture of normal distributions. Manuscript profile -
Open Access Article
495 - Designing non-linear pattern contagious influence of the Tehran Price Index from the physical assets market (Application of NARX artificial neural network model)
mahdi shaban habibollah nakhaei Ghodrat Alloh Talebnia nazanin bashirimaneshThe present study examines the contagiousness of the Tehran Stock Exchange from the price of parallel assets using the dynamic neural network. To perform calculations, the time series of coin price variables as a representative of the gold market, the average price per MoreThe present study examines the contagiousness of the Tehran Stock Exchange from the price of parallel assets using the dynamic neural network. To perform calculations, the time series of coin price variables as a representative of the gold market, the average price per square meter of residential building as a representative of the housing market. The price of each barrel of Iranian crude oil and the US dollar exchange rate and their conditional fluctuations as explanatory variables and the total index of Tehran Stock Exchange and its conditional fluctuation as the target variable from 1387 to 1397 are examined daily .The dynamic neural network is evaluated with four input variables and one target variable with different neurons with the MSE criteria, and the models with 20 neurons and 10 neurons have the lowest MSE, .Research results show that the stock exchange has a maximum of two lag from competing markets has become contagious, indicating the poor performance of the Tehran Stock Exchange. The results show that the proposed neural network patterns have a high power in predicting the index of Tehran Stock Exchange and its fluctuations from 1387 to 1397 as in-sample forecast and in 1398 as extra-sample forecast. Manuscript profile -
Open Access Article
496 - The Impact of Using Dimensionality Trading Strategies on Forecasting the Daily Stock Returns of the Panel Data Method.
Ehteram Rahdarpoor heshmatolah asgariEarnings forecasting systems provide timely decisions by providing timely information. Earnings forecasting by management is widely used in assessing profitability, profit-related risk, stock price judgments, and valuation models (Manfred & Inky, 2014). Our purpose MoreEarnings forecasting systems provide timely decisions by providing timely information. Earnings forecasting by management is widely used in assessing profitability, profit-related risk, stock price judgments, and valuation models (Manfred & Inky, 2014). Our purpose in this study is to investigate and investigate the impact of dimensionality trading strategies on predicting daily stock market returns by the fuzzy logic approach of firms. This study is a library-analytic-causal study based on panel data analysis (panel data). In this study, the financial information of 19 companies listed in Tehran Stock Exchange during the period 2011-2018 was reviewed. The results showed that using stock trading strategy and stock price reduction strategy have significant effect on prediction of daily stock market returns, but trading volume reduction strategy has no significant effect on market forecasting. I hope to accept my article. I suggest the editor remove this restriction on the number of words used in the abstract for the English text. Manuscript profile -
Open Access Article
497 - Design of Decision Support System to Forecast Demand for Dynamic Network Design Based on Uncertainty and its Impact on Economic Justification
Mohammad Mokhtari Aboutorab Alirezaei Hassan Javanshir Mahmoud ModiriMinimize supply chain costs as one of the essential issues in support activities such as financial planning systems,How to manage supply chain A set of ways to integrate Effective suppliers, manufacturers, warehouses and stores used to minimize total supply chain costs MoreMinimize supply chain costs as one of the essential issues in support activities such as financial planning systems,How to manage supply chain A set of ways to integrate Effective suppliers, manufacturers, warehouses and stores used to minimize total supply chain costs and meet customer service needs with a high level of service. In this study, the design of a robust cement supply chain dynamic network model was designed to reduce supply chain management costs after a crisis. Principal and efficient design of cement grid infrastructures, given the strong demand fluctuations at different times of the year, can significantly reduce financial costs on the one hand and reduce the potential for high-speed, high-cost corruption by correct prediction. Other leads.From the following tool The nose has been analyzed using artificial neural networks. The purpose of this study is to use artificial intelligence methodologies such as Grid Clustering, Subtractive Partitioning, FCM to explore fundamental and technical patterns and relationships in historical data. Used. To this end, a genetically-based inference fuzzy multilayer fuzzy neural network is introduced to prevent technical and economic unpredictability. The basic model of this paper presented by the researcher is a robust and multi-periodic planning for multi-product state under uncertainty. Manuscript profile -
Open Access Article
498 - Designing a Model for Forecasting the Stock Exchange Total Index Returns (Emphasizing on Combined Deep Learning Network Models and GARCH Family Models)
Mehdi Zolfaghari Bahram Sahabi Mohamad javad BakhtyaranGiven the development of machine learning models in predicting financial data in recent years, this study introduces a combination of Deep Learning Network and selected GARCH family models to predict short-term daily returns of the Tehran Stock Exchange Index. The most MoreGiven the development of machine learning models in predicting financial data in recent years, this study introduces a combination of Deep Learning Network and selected GARCH family models to predict short-term daily returns of the Tehran Stock Exchange Index. The most important feature of the deep learning network is that it can adapt and adjust itself to the volatility of market variables without being limited to specific models. In this study, short-term and long-term memory based neural network (RNN-LSTM) models are used for deep learning network models and GARCH and EGARCH models are used in its structure. Also, the two independent variables of oil price and dollar rate in the structure of the hybrid model help to predict the financial data more accurately. Comparison of the results of hybrid model prediction error with individual models shows that the RNN-LSTM-EGARCH hybrid model has higher prediction accuracy than competing models. competing models. Manuscript profile -
Open Access Article
499 - Stock Price Prediction in Tehran Stock Exchange Using Artificial Neural Network Model and ARIMA Model: A Case Study of Two Active Pharmaceutical Companies in Stock Exchange
Ahmad Chegeni AZIZ GORDIn This Study We Compare the Efficiency of Both Artificial Neural Network Prediction Methods (ANN) and Traditional Method of Auto Regressive Integrated Moving Average (ARIMA) in Predicting Stock Prices in Iranian Stock Market. For This Purpose, Four Pharmaceutical Compa MoreIn This Study We Compare the Efficiency of Both Artificial Neural Network Prediction Methods (ANN) and Traditional Method of Auto Regressive Integrated Moving Average (ARIMA) in Predicting Stock Prices in Iranian Stock Market. For This Purpose, Four Pharmaceutical Companies, Alborz Drug, Iran Drug, Pars Drug, and Jam Drug Were Selected and ARIMA Model and Artificial Neural Network Model Were Estimated For All Four Companies. In Order to Estimate Artificial Neural Network Model, Stock Price Variable as Dependent Variable and Stock Trading Volume, Drug Industry Index, OPEC Oil Price, Exchange Rate and Gold Price are Considered as Independent Variables. MSE, RMSE, MAD, R2 and MAPE Criteria Were Used to Compare Two Models. In Order to Estimate the Stock Price Forecast Regression Model, Use of Auto Regressive Integrated Moving Average (ARIMA) Regression Is Used and Estimation of the Coefficients of the Model is Performed Using the EVIEWS Statistical Software. An Suitable ANN Model Was Created For Predicting Stock Prices Using MATLAB Software. The Results of the Research Showed That the Research Hypothesis is Correct and the Artificial Neural Network Model (ANN) Has a Better Predictor of Stock Price in the Iranian Stock Market Than the ARIMA Method. Manuscript profile -
Open Access Article
500 - Modeling of exchange rate fluctuations with systems dynamics approach
mohammad hadi damiri parviz saeedi Hosein Didehkhani ebrahim abbasiAbstract The purpose of this research is Modeling of exchange rate fluctuations with systems dynamics approach. In this research, all the factors affecting the exchange rate have been identified and evaluated their systemic relationships. First, the trend and the exchan MoreAbstract The purpose of this research is Modeling of exchange rate fluctuations with systems dynamics approach. In this research, all the factors affecting the exchange rate have been identified and evaluated their systemic relationships. First, the trend and the exchange rate price were predicted using the system dynamics from 2004 to 2022 , and the results were compared with the trend and real exchange rate of the exchange rate. The results show that the exchange rate trend over the 19-year period has always been with a slight upward slope, but during the years 2012 -2013 and 2018-2017 there was a sharp rise in price and slope that is exactly the same as the real exchange rate trend. Also, comparing the exchange rate data to the market price and the expected exchange rate until 2018 shows that this model has been able to accurately assess the trend and predict possible failures. Key word: Exchange rate, system dynamics, forecast, trend. Manuscript profile -
Open Access Article
501 - The Comparison of Cryptocurrency Returns Prediction Based on Geometric Brownian Motion and Wavelet Transform
Ahmad Shojaei Alireza Heidarzadeh HanzaeiIn the present study the accuracy of predicting cryptocurrencies return was compared through two approaches of Geometric Broanian Motion (GBM) and Wavelet Transforms (WT). In order to do that, 5 cryptocurrencies of BTC, ETH, XRP, BCH and EOS as representatives of risky MoreIn the present study the accuracy of predicting cryptocurrencies return was compared through two approaches of Geometric Broanian Motion (GBM) and Wavelet Transforms (WT). In order to do that, 5 cryptocurrencies of BTC, ETH, XRP, BCH and EOS as representatives of risky assets were studied with daily frequency during the one year period of 2018 to 2019. Two measures of RMSE and MAE were employed to compare the accuracy of approaches in prediction of returns. In geometric Brownian modeling, the Brownian process-based stochastic differential model for asset prices leads to the fact that the logarithmic return of an asset has a normal distribution with time-dependent parameters. The results of logarithmic returns prediction by both of methods showed that WTs have less error than GBM in returns prediction of BTC, ETH, XRP and BCH cryptocurrencies and for each of accuracy measures, an specific approach has desirable performance for prediction of EOS returns. citing these results it can be concluded that WT in prediction of risky assts returns has less error than GBM method. Manuscript profile -
Open Access Article
502 - Stock price forecasting using a hybrid model based on recurring neural network and ANFIS and fuzzy expert system
Mostafa Yousofi Tezerjan Azam dokht Safi Samghabadi Azizollah MemarianiStock price forecasting is a challenging and attractive topic. Investors are interested in being able to predict the price of different stocks in financial markets. This paper presents a hybrid model that predicts the final stock price for the next day based on the adap MoreStock price forecasting is a challenging and attractive topic. Investors are interested in being able to predict the price of different stocks in financial markets. This paper presents a hybrid model that predicts the final stock price for the next day based on the adaptive neuro-fuzzy inference systems (ANFIS) and Return Neural Network (RNN) algorithm using historical data and indicators. Then the results of this model and the status of market rumors enter the fuzzy expert system based on the output of the fuzzy neural system and the return neural network along with the market rumor status and finalize the forecast. The combined model proposed to predict the stock price data of Mobarakeh Steel Company of Isfahan was implemented. In this study, for research data, the data of Tehran Stock Exchange Company related to the stock data of Mobarakeh Steel Company of Isfahan from April 26, 2016 to March 20, 2017 has been used. Four technical indicators used in this study are: Moving Average(MA), Exponential Moving Average(EMA), Relative Strength Index(RSI), and Moving Average Convergence Divergence(MACD). These variables have been used as the input of the adaptive neuro-fuzzy inference systems(ANFIS) to predict the final price of the next day's shares. Manuscript profile -
Open Access Article
503 - Predicting Capital Market Returns Using the Learning Model of Levenberg-Marquardt, Gradient descent and ARIMA Algorithm
mehdi asharion ghomizadeh mohammad mahmoodiThe present study compares and predicts the predictive ability of the capital market based on the learning pattern of the Levenberg-Marquardt algorithm, the Gradient descent and the ARIMA Algorithm. For this purpose, market data were used in the period from 1394 to 1397 MoreThe present study compares and predicts the predictive ability of the capital market based on the learning pattern of the Levenberg-Marquardt algorithm, the Gradient descent and the ARIMA Algorithm. For this purpose, market data were used in the period from 1394 to 1397, and more than 75% of these data were used as training data prior to 1397, and one year end data were used as data. The results of the evaluation of the research data show that artificial neural networks have a high capacity for price prediction.The results also showed that in both training data series from 1394 to 1396 and experimental of 1397 the comparison of the results and performance of ARIMA neural networks (ARIMA) showed that the neural network had higher predictive power in Comparing with the performance and prediction accuracy of two types of neural networks with the Levenberg-Marquardt learning algorithm and the Gradient descent learning algorithm using the Levenberg-Marquardt learning algorithm has been able to increase the neural network prediction accuracy And reduce its error, so, the results of the present study show, the Levenberg-Marquardt learning algorithm improves the predictive power of the neural network. Manuscript profile -
Open Access Article
504 - Imaged financial Ratios and Bankruptcy Prediction using Convolutional Neural Networks
abbasali haghparast alireza momeni Aziz Gord fardin mansooriConvolutional neural networks are being applied to identification problems in a variety of fields, and in some areas are showing higher discrimination accuracies than conventional methods. Hence, in this research, an attempt is made to apply a convolutional neural network MoreConvolutional neural networks are being applied to identification problems in a variety of fields, and in some areas are showing higher discrimination accuracies than conventional methods. Hence, in this research, an attempt is made to apply a convolutional neural network to the prediction of corporate bankruptcy. The financial statements ratios has been choice 66 companies that have been delisted from the Iran Stock Market due to de facto bankruptcy as well as the financial statements of 66 listed companies over 2000 to 2019 financial periods. In this method, a set of financial ratios are derived from the financial statements and represented as a grayscale image. The image generated by this process is utilized for training and testing a convolutional neural network. The images for the bankrupt and continuing enterprises classes are used for training the convolutional neural network based on GoogLeNet. The findings shows, in prediction of going concern of firms, Convolutional neural network has predicted with 50 percent of precision. This means that 50 percent of continues firms and 50 percent of bankrupt firms has been predicted precisely. Manuscript profile -
Open Access Article
505 - Comparison of the performance of Merton and Heston models in predicting the price of gold coin futures contracts
Rahele Baqeri mohammadreza setayeshToday, investing in gold markets is an important part of any country's economy, so estimating the price of gold is one of the most important topics of study for economists and financial analysts who have developed different approaches and perspectives. Naturally, method MoreToday, investing in gold markets is an important part of any country's economy, so estimating the price of gold is one of the most important topics of study for economists and financial analysts who have developed different approaches and perspectives. Naturally, methods can be durable and suitable for use that have the least investment error and risk. In developing countries such as Iran, due to inflation and uncertainty about the future, the demand for gold to cover the risk of inflation is high.The formation of the Bahar Azadi coin futures contract market in the Commodity Exchange in recent years has also helped to create an organized market to cover risk and also to use arbitrage opportunities in the gold market. The trading statistics of Bahar Azadi coin futures contract have grown significantly since the entry of its first symbol in the trading table of Iran Commodity Exchange, so that it has created an organized market with high trading volume and appropriate liquidity in the field of derivatives trading in the country. In this study, we decided to use two models of stochastic differential equations (Heston and Merton) to predict the price of futures contracts and compare the results. Manuscript profile -
Open Access Article
506 - Designing a model for predicting bitcoin returns (with emphasis on hybrid models of convolutional and recursive neural networks and models with long-term memory)
Mohammad Javad Bakhtiaran Mehdi ZolfaghariFinding the best way to optimize the portfolio is one of the concerns of activists in the investment management industry. In recent years, the introduction of economic and mathematical models in the prediction of Bitcoin has helped many investors to optimize portfolios. MoreFinding the best way to optimize the portfolio is one of the concerns of activists in the investment management industry. In recent years, the introduction of economic and mathematical models in the prediction of Bitcoin has helped many investors to optimize portfolios. Therefore, in this study, we introduce models of GARCH family composition and recurrent and convolutional neural network to predict the daily yield of Bitcoin will be paid during the period of 1398-1392. In this study, the Bitcoin is examined using GARCH and EGARCH short-term memory models. Of the two variables, the price of crude oil and the Gold as factors that their shocks and fluctuations have a major impact on Bitcoin are used as control variables. In addition to using long-term memory models, considering the better performance of combined models (compared to individual models) In anticipation In this study, all models of the GARCH family (both short and long run) with the recurrent and convolutional neural network were combined and using the combined models, the efficiency of the Bitcoin for the next 10 days were predicted step by step and its accuracy Based on the evaluation criteria. Manuscript profile -
Open Access Article
507 - Designing a Model for Forecasting the Gold Price Returns (Emphasizing on Combined convolutional neural network Models and GARCH Family Models)
Mohammad Javad Bakhtiaran mehdi ZolfaghariFinding the best way to optimize the portfolio is one of the concerns of activists in the investment management industry. In recent years, the introduction of economic and mathematical models in the prediction of Gold indice has helped many investors to optimize portfol MoreFinding the best way to optimize the portfolio is one of the concerns of activists in the investment management industry. In recent years, the introduction of economic and mathematical models in the prediction of Gold indice has helped many investors to optimize portfolios. Therefore, in this study, we introduce models of GARCH family composition and convoultional neural network to predict the daily yield of Gold index will be paid during the period of 1390-1398. In this study, the Gold index is examined using GARCH and EGARCH short-term memory models. Of the two variables, the price of crude oil and the dollar index as factors that their shocks and fluctuations have a major impact on Gold indices are used as control variables. In addition to using convolutional model, considering the better performance of combined models (compared to individual models ) In anticipation In this study, all models of the GARCH family (both short and long run) with the convoultional neural network were combined and using the combined models, the efficiency of the main stock index and the five selected indicators for the next 10 days were predicted step by step and its accuracy Based on the evaluation criteria. Manuscript profile -
Open Access Article
508 - Presentation Optimization portfolio model from market index prediction model despite of the long term memory with neural network
saeed moshtagh Farhad Hosseinzadeh Lotfi Esmail fadayi nezhadThe effect economic variables at investment markets is the important subject in financial theory. Tehran stock exchange to have special position in country financial system and efficiency development investment market is dependent being active this constitution in count MoreThe effect economic variables at investment markets is the important subject in financial theory. Tehran stock exchange to have special position in country financial system and efficiency development investment market is dependent being active this constitution in country. Two important function Tehran exchange market are gathering small savings and available liquidity in society and guide them to production process in country. In this way presentation optimization portfolio model from market index prediction model and exchange return rate is impact. One of the tools with high accuracy and applicable for predicting was neural network why so accuracy isnot decrease with increasing thesis data and its accuracy was very higher than regeression, linear and non linear for prediction. After some tests from artificial neural network and adaptive neuro fuzzy inference system and support vector regression with matlab software has been done. We design a model with high accurancy for predicting rate of liquidity index and total return index and then we design Ideal optimization portfolio. Manuscript profile -
Open Access Article
509 - Prediction of Tehran Stock Exchange Total Index Using Bacterial Foraging OptimizationAlgorithm
ahmad nateq golestanIt is impossible to advance the economic goals of any country without financial markets. Since the stock exchange is one of the most important financial markets in the country, and the stock index is one of the important parameters in determining it,s performance, So th MoreIt is impossible to advance the economic goals of any country without financial markets. Since the stock exchange is one of the most important financial markets in the country, and the stock index is one of the important parameters in determining it,s performance, So the stock index and economic development have an important interconnected relationship. Stock market forecasting has been considered as one of the most challenging financial issues and the accuracy of these forecasts is crucial for improving trading and investment strategies in the stock market. The total price of Tehran stock exchange price using intelligent methods. An optimization Bacterial Foraging Optimization Algorithm has been for modeling. In this research, the total index of Tehran stock exchange price data for the 23rd March 2006 to 21rd March 2018. Ten using the total price index data (consists of the highest price, lowest price, closing price and total volume of stocks traded for the day) and finally, by Matlab software, the forecast price index waz calculated. The results of the research show that the algorithm has the accuracy of ninety seven percent ability to predict the total index price of the stock exchange. Manuscript profile -
Open Access Article
510 - Ranking of banks based on CAMELS indicators to predict financial distress by logistic regression and Data Envelopment Analysis
Gholam abbas Paidar Morteza Shafiee Fariborz Avazzadeh Fath Hashem ValipoorIt is very important to choose an efficient monitoring system to assess the financial distress of banks, therefore, one of the most important monitoring systems used to assess the financial distress of banks is the CAMELS monitoring system. Which includes six indicators MoreIt is very important to choose an efficient monitoring system to assess the financial distress of banks, therefore, one of the most important monitoring systems used to assess the financial distress of banks is the CAMELS monitoring system. Which includes six indicators; Capital adequacy, asset quality, management quality, revenue quality, liquidity, market risk sensitivity. Therefore, in this study, the criterion of financial helplessness of banks is CAMELS indicators. Initially, 17 banks listed on the Tehran Stock Exchange in the fiscal year 1399 were ranked and divided into healthy and helpless financial groups by CAMELS indicators. Then, models, Data Envelopment Analysis and logistic Regression were used to predict the financial distress of banks. Then, with the pairwise comparison test (T), the prediction accuracy of both models was investigated. In logistic regression method, binary model with ForwardlR method was used. And in data envelopment analysis method, SBM model with different application was used. The results showed that the overall accuracy of the logistic regression model is higher than the data envelopment analysis model in assessing financial distress and also the CAMELS monitoring system can be a good assessor for banks' financial distress. Manuscript profile -
Open Access Article
511 - Comparison of different machine learning models in stock market index forecasting
maryam sohrabi Seyed Mozaffar mirbargkar Ebrahim Chirani SINA KHERADYARPredicting time series of financial markets is a challenging issue in the field of specialized studies of time series and has attracted the attention of many researchers. Due to the presence of big data, this issue has led to the growth of developments in the field of m MorePredicting time series of financial markets is a challenging issue in the field of specialized studies of time series and has attracted the attention of many researchers. Due to the presence of big data, this issue has led to the growth of developments in the field of machine learning models. Due to the importance of this issue, in this study, by using the comparison of different machine learning models such as random forest approaches, support vector machine, artificial neural network and deep learning-based recurrent neural networks to investigate the ability of different machine learning models in prediction. The total index of Tehran Stock Exchange during the period 2013 to 2020 has been discussed. The prediction results of 1, 3 and 6 day courses for the out-of-sample period show that the machine learning method based on the long short-term memory (LSTM) network, a recurrent neural networks, has a better result compared to other models. Manuscript profile -
Open Access Article
512 - A model for predicting stock price reaction delays based on grounded theory
kyvan faramarzi jamal bahrisales Saeed Jabbarzadeh Kangarlouie ali ashtabThe aim of current study was to provide a model for predicting stock price reaction delay based on grounded theory. In the present study,semi-structured interviews have been used as data collection tools and snowball or chain sampling methods and purposeful sampling has MoreThe aim of current study was to provide a model for predicting stock price reaction delay based on grounded theory. In the present study,semi-structured interviews have been used as data collection tools and snowball or chain sampling methods and purposeful sampling has been used to select the sample which based on the principle of theoretical adequacy The research data were analyzed using open, axial and selective coding. Results: In this study, based on 42 conducted interviews, a total of 607 interview codes, 101 sub-categories (concepts) and 11 main categories were extracted. Then the qualitative model of the research is designed and based on the analysis of data (interviews) the link between the categories in the form of causal conditions, contextual conditions, intervening conditions, strategies and consequences has been conducted. The results indicated that macro factors and market shareholders are effective in predicting the stock price reaction delay.On the other hand, according to these affecting factors, strategies to improve the stock price reaction delay prediction, including the establishment of corporate information and financial statements, corporate information, market performance criteria, management and corporate control which are aroused in the context of affecting factors and interferers, are presented. Manuscript profile -
Open Access Article
513 - Investigating the Dynamic relations between the Trend of Tehran Stock Exchange’s index and the Cumulative Funds' Cash Flow".
mirfeiz fallah Amirhosseyn shamaeezadehThe purpose of this study is to investigate the relationship between the net cash flows of the Tehran Stock Exchange funds and the Tehran Stock Exchange index during the period of 2013 to December 2019, using the information of the 10 largest active mutual funds establi MoreThe purpose of this study is to investigate the relationship between the net cash flows of the Tehran Stock Exchange funds and the Tehran Stock Exchange index during the period of 2013 to December 2019, using the information of the 10 largest active mutual funds established and active in the Tehran Stock Exchange during this period. .In this study, an index of net cash flows into mutual funds daily and cumulatively is considered as a measure of cash flow compared to the TSE Index (TEDPIX). The results of this test indicate that the two indices are coherent in series and their relationships are significant in the long run. Also, the Granger causality test was used to examine the interrelationships between these two indices.The results of this test showed that there is an interaction between the two indices. This means that in the long run, both indices affect each other so net cash inflows to the funds can be a measure for predicting the overall indices trend but with Attention to the behavioral errors identified in similar articles.for predicting the index cannot be relied solely on net cash inflows into the funds. Manuscript profile -
Open Access Article
514 - The Assessment of the optimal Deep Learning Algorithm on Stock Price Prediction (Long Short-Term Memory Approach)
Amir Sharif far Maryam Khalili Araghi Iman Raeesi Vanani Mirfeiz FallahForecasting stock prices plays an important role in setting a trading strategy or determining the appropriate timing for buying or selling a stock. Deep Learning (DL) is a type of Artificial Neural Network (ANN) that consists of multiple processing layers and enables hi MoreForecasting stock prices plays an important role in setting a trading strategy or determining the appropriate timing for buying or selling a stock. Deep Learning (DL) is a type of Artificial Neural Network (ANN) that consists of multiple processing layers and enables high-level abstraction to model data. The key advantage of DL models is extracting the good features of input data automatically using a general-purpose learning procedure which is suitable for dynamic time series such as stock price.In this research the ability of Long Short-Term Memory (LSTM) to predict the stock price is studied; moreover, the factors that have significant effects on the stock price is classified and legal and natural person trading is introduced as an important factor which has influence on the stock price. Price data, technical indexes and legal and natural person trading is used as an input data for running the model. The results obtained from LSTM with Dropout layer are better and more stable than simple form of LSTM and RNN models. Manuscript profile -
Open Access Article
515 - Estimation of a model for predicting the trend of digital currencies (Bitcoin, Ethereum) in the corona and post-corona periods with the help of time series
Seyed Ramin Saeedi nezhad sina lalehAfter the broadcast world and the epidemic of pandemic covid-19 was a severe economic crisis, For this reason, the need for more prediction became apparent. One of these methods is time series prediction. In this study, first, the effect of covid-19 disease on price of MoreAfter the broadcast world and the epidemic of pandemic covid-19 was a severe economic crisis, For this reason, the need for more prediction became apparent. One of these methods is time series prediction. In this study, first, the effect of covid-19 disease on price of Ethereum and Bitcoin, and the results show that this disease had a negative effect on world prices of Ethereum and Bitcoin. In the next step, using univariate time series methods and with the help of ARIMA models, a model for predicting which is the best model AR (1) and MA(1) and time differentiation was designed, the one-year and two-year forecasts were done with the designed model. According to the reports of the World Health Organization, there is probably corona pandamic for up to one year, and For the next two years, Corona has emerged from a pandemic is called the post-corona period. The results show that After a short decline and reacting to resistance and support, they will have an annual upward trend. Manuscript profile -
Open Access Article
516 - Using Brownian motion in stock prices prediction in comparison with ARIMA
farhad karimiasl ali saeydy heidar foroghneghad mohammad kodaei voleh zaghrdThe main reason that people invest in the stock market is to earn profits that require having accurate market information and stock changes and predicting its future trend. Therefore, the investor needs the powerful and reliable tools needed to predict stock prices. In MoreThe main reason that people invest in the stock market is to earn profits that require having accurate market information and stock changes and predicting its future trend. Therefore, the investor needs the powerful and reliable tools needed to predict stock prices. In this regard, the present study investigates stock price forecasts based on MSE mean square error, mean absolute deviation MAE and root mean square error RMSE. Finally, the methods investigated in this study are compared and identify the top method to predict stock prices. For this purpose, the data of the top 50 stock exchange companies, which are quarterly presented by the stock exchange organization, were used during the period 2012-2018. In order to test the research hypotheses, linear regression method, Brownian method and ARIMA method were used. The research findings show that the Brownian model predicts stock prices more accurately than the ARIMA method. It was also observed that linear statistical ARIMA models are less efficient in the financial markets than the brownian methods. Manuscript profile -
Open Access Article
517 - Predicting the daily index of the Tehran Stock Exchange using the selection of appropriate features for the Long Short-Term Memory neural network (LSTM)
Somayeh Mohebi Mohammad Esmaeil Fadaeinejad mohammad osoolian Mohammad reza HamidizadehThe stock market index is one of the effective features in investment because it can well reflect the health status and macro change trend of a country’s economic development. Various features affect the stock index. The various combinations of these features crea MoreThe stock market index is one of the effective features in investment because it can well reflect the health status and macro change trend of a country’s economic development. Various features affect the stock index. The various combinations of these features create a wide state space. Hence, it is impractical to provide a data set containing all these combinations to train the stock index prediction model. in this research, an attempt has been made, after collecting a significant number of effective features on the index, to provide a method for selecting appropriate features for the stock index prediction model with aim of increasing prediction accuracy. For this purpose, the mRMR algorithm is used as the basic algorithm. Also, to select the appropriate model, a number of the most applicable artificial intelligence models for predicting the stock index were compared and according to the results, the LSTM network was selected to predict the stock index. The results of this study show that using the LSTM network and the proposed method in selecting features, with 8 selected features, high accuracy can be achieved in the daily prediction of the Tehran Stock Exchange Index. So that MPE is calculated to be about 2.66, Manuscript profile -
Open Access Article
518 - A prediction-based portfolio optimization model using support vector regression
Mohammad Amin Monadi Amirabbas NajafiThe purpose of portfolio optimization is to select an optimal combination of financial assets, which should be a guide for investors to achieve the highest returns against the lowest possible risk. On the other hand, one of the key factors in portfolio optimization deci MoreThe purpose of portfolio optimization is to select an optimal combination of financial assets, which should be a guide for investors to achieve the highest returns against the lowest possible risk. On the other hand, one of the key factors in portfolio optimization decisions is related to predict the stock prices. To do this, classical nonlinear mathematical and intelligent models such as regression are commonly used. In the present study, a nonlinear model of support vector regression with multiple outputs is applied to reduce the prediction errors. To show the effectiveness of the proposed model, the data of S & P500 index companies in the period 12/09/2016 to 02/08/2021 is used. The results show that the selection of a portfolio based on prediction using multiple vector backup regression due to considering the relationships between outputs simultaneously in terms of Sharp criteria has a better performance than the selection of portfolio based on prediction using regression method. Manuscript profile -
Open Access Article
519 - Comparison of the Predictive Accuracy of Artificial Neural Network Systems Based on Multilayer Perceptron Approach and Falmer Binary-Logistics Model in Order to Predict Bankruptcy
Somieh Saroei Hamid Reza Vkili Fard, Ghodratolah Taleb NiaFinancial analysts and other users need relevant and reliable information to predict corporate bankruptcy, which should be distributed symmetrically to all users. Accordingly, the purpose of this study is to compare the prediction accuracy of Artificial Neural Network ( MoreFinancial analysts and other users need relevant and reliable information to predict corporate bankruptcy, which should be distributed symmetrically to all users. Accordingly, the purpose of this study is to compare the prediction accuracy of Artificial Neural Network (ANN) systems based on the Multilayer Perceptron Approach and Falmer Binary-Logistics Model in order to predict bankruptcy. To test the hypotheses, the combined data of 172 companies listed on the Tehran Stock Exchange in the period 2007-2016 were used. The results of the analysis of the research data show that the ANN system can identify of the factors affecting on bankruptcy of Iranian companies in the year before bankruptcy by Precision equal 98%. Findings from the binary-logistic model showed that the forecasting model designed based on the Falmer regression method is able to predict with 82% accuracy the bankruptcy of the sample companies. Therefore, the use of artificial neural networks can more powerfully and accurately predict bankruptcy than regression models. Manuscript profile -
Open Access Article
520 - Deep learning for stock market forecasting using numerical and textual information (Long-Short Term Memory approach)
seyyedeh mozhgan beheshti masalegou Mohammad ali Afshar kazemi jalal Haghighat monfared Ali RezaeianStock prices are influenced by many factors, making forecasting challenging. This prediction is often ineffective if it only considers numerical data or textual information. This research aims to provide a method of forecasting the future price of stocks based on the st MoreStock prices are influenced by many factors, making forecasting challenging. This prediction is often ineffective if it only considers numerical data or textual information. This research aims to provide a method of forecasting the future price of stocks based on the structure of a deep neural network using price data, a set of technical indicators, and news headlines as input to the model. For this purpose, Dow Jones stock data and Reddit channel news data have been used. Technical features are extracted from the stock data, and the news data are converted into a feature vector by the Bag of Words method and fed into the Long-Short term memory network for prediction. Accuracy is used as a performance evaluation measure and experiments on two data sets. The only numerical and only text has been used to evaluate the simultaneous use of two information sources. Also, three networks, SVM, MLP, and RNN, have been used to evaluate the model. The results show that the LSTM model achieved the highest prediction accuracy of 69.19% using news and financial data. News data is 65.62% accurate, and numerical data is 51.89%. Also, the LSTM model performs better than SVM, MLP, and RNN neural networks. Manuscript profile -
Open Access Article
521 - Solving Imbalanced Data Distribution Problem in Bankruptcy Prediction by Cost-Sensitive Learning Method
seyed behrooz razavi ebrahim abbasiThis study aimed to add cost-sensitive learning technique to imbalanced data-based bankruptcy prediction models in order to reduce type I error and increase the geometric mean criterion of overall accuracy to reduce the misclassification costs of bankrupt companies for MoreThis study aimed to add cost-sensitive learning technique to imbalanced data-based bankruptcy prediction models in order to reduce type I error and increase the geometric mean criterion of overall accuracy to reduce the misclassification costs of bankrupt companies for stakeholders. For this purpose, type I error, type II error, and the geometric mean of overall accuracy of bankruptcy models based on cost-sensitive learning were compared with bankruptcy prediction models with highly imbalanced datasets. The statistical sample included 1200 year-companies since 2001- 2020, consisting of 90% healthy companies and 10% bankrupt companies. Hypotheses test results showed that adding a cost-sensitive learning technique to the bankruptcy prediction models led to a significant decrease in the type I error, a significant increase in the type II error, and a significant increase in geometric mean of accuracy of imbalanced data-based models at 95% confidence level. Also, with the increase in the misclassification cost of bankrupt companies, type I error had a downward trend and the II type error had an upward trend, and the geometric mean of accuracy had an upward trend. Manuscript profile -
Open Access Article
522 - Presenting a market direction prediction model for gold coin trades in Iran’s Commodity Exchange market using Long Short-Term Memory (LSTM) algorithm
Soheil Zoghi Reza Raei Saeed FalahporIn recent years, deep learning neural networks have been recognized as powerful tools for solving complex problems. Deep learning is a subfield of artificial intelligence in which complex problems with numerous parameters and inputs are modeled based on a set of algorit MoreIn recent years, deep learning neural networks have been recognized as powerful tools for solving complex problems. Deep learning is a subfield of artificial intelligence in which complex problems with numerous parameters and inputs are modeled based on a set of algorithms. In this research, a new framework of deep learning is presented. Using wavelet transform, stacked auto-encoders, and the Long Short-Term Memory or LSTM, we predict the market direction in the future contracts of gold coins of Iran's Commodity Exchange market. The input data is first denoised using the wavelet transformer in the proposed method. Then, using the stacked auto-encoder, the indicators influencing the market direction are identified. Ultimately, these indicators are given as input to the LSTM architecture to predict the market direction. Proposing several new technical indicators to increase the accuracy of the proposed model, adjusting the parameters of the utilized algorithms, including LSTM, for this problem, and suggesting a trading strategy to achieve appropriate profitability are among the contributions of the present study. Investigations reveal that the proposed method outperforms other approaches and achieves higher accuracy and efficiency. Manuscript profile -
Open Access Article
523 - Price predicting with LSTM artificial neural network and portfolio selection model of financial assets and digital currencies
Faranak Khonsarian Babak teimourpour Mohammad Ali RastegarFinding solutions for price prediction, forming an optimal portfolio and achieving more profit are the basic goals of financial market activists. The purpose of this research is to predict the price of financial assets such as several stocks, gold, coin and a number of MoreFinding solutions for price prediction, forming an optimal portfolio and achieving more profit are the basic goals of financial market activists. The purpose of this research is to predict the price of financial assets such as several stocks, gold, coin and a number of digital currencies using the LSTM neural network model and then form an optimal portfolio by calculating the rate of return, risk and the Sharpe ratio. The data used is from the archives of the Tehran Stock Exchange website, the website of the gold, coin and currency information network, as well as the website of buying and selling digital currencies. The time series of the prices of the investigated assets is between 2017 and 2020. Also, we used Python programming language and Gephi software to build the model and analyze the data. In the end, it was found that the LSTM neural network model is capable of predicting the price of financial assets with a very low error rate in each asset, and according to the Sharpe ratio obtained for each financial asset and the correlation matrix, Vebank stock, Khbahman 1 stock, and Digital currencies TRON, Tether and Bitcoin allocate more shares in the proposed portfolio. Manuscript profile -
Open Access Article
524 - Comparison of multiple linear regression and machine learning algorithms inPredicting cash holdings
samira seif mostafa yousofi tezerjanIn recent years, in the financial literature, more attention has been paid to the level of cash holding of companies. So; Forecasting is important to determine the optimal level of cash holding. In this research, using linear and non-linear methods and 13 influential in MoreIn recent years, in the financial literature, more attention has been paid to the level of cash holding of companies. So; Forecasting is important to determine the optimal level of cash holding. In this research, using linear and non-linear methods and 13 influential input variables, the amount of cash in 103 companies admitted to the Iran Stock Exchange during the years 2013 to 2021 has been predicted. The methods used include multiple linear regression (MLR), k nearest neighbor (KNN), support vector machine (SVM) and multi-layer neural networks (MLNN) for prediction. The results show that the traditional method of multiple linear regression has not been successful in predicting cash, but machine learning algorithms have been superior with an accuracy of 0.99. The variables of profit per share, the ratio of current assets to current liabilities and the ratio of short-term debt to total assets have had a greater impact in all algorithms. Therefore, managers can use advanced machine learning algorithms to predict the future cash flow of companies. Manuscript profile -
Open Access Article
525 - Bankruptcy prediction using hybrid data mining models based on misclassification penalty
Atiye Torkaman AmirAbbas NajafiIn recent years, data mining, particularly the support vector machine, has gained considerable interest among investors, managers, and researchers as an effective means of bankruptcy prediction. However, studies indicate that it is highly sensitive to the selection of p MoreIn recent years, data mining, particularly the support vector machine, has gained considerable interest among investors, managers, and researchers as an effective means of bankruptcy prediction. However, studies indicate that it is highly sensitive to the selection of parameters and input variables. Hence, the aim of this research is to improve bankruptcy prediction accuracy by combining an advanced support vector machine model with the k-nearest neighbor approach to eliminate erroneous entries. To achieve this, first, by using five financial ratios: current ratio, net profit margin, debt ratio, return on assets, and return of investment from 150 companies listed on the Tehran Stock Exchange during the 10-year period (2010-2019), and k-nearest neighbor algorithm, the training data will be refined. Then, relying on a support vector machine based on classification penalty, a prediction model will be constructed. The parameters will be estimated, and its validity will be assessed using test data. Finally, a comparison will be made between the outcomes of the proposed model and traditional models.The findings demonstrate that the combination of the k-nearest neighbor models and support vector machine reduces the overall prediction error, and the penalty coefficients of the support vector machine exhibit a high level of statistical significance. Manuscript profile -
Open Access Article
526 - A trading algorithm to establish a suitable investment system with a reasonable return (Case study: Tehran Stock Exchange)
Hassan Torabi Mehdi Bararnia firouzjaeiOne of the most important issues in modern financial markets is finding efficient ways to summarize and visualize stock market information. The purpose of this paper is to discover a method to reduce risk and increase investment returns. By analyzing the mass volume of MoreOne of the most important issues in modern financial markets is finding efficient ways to summarize and visualize stock market information. The purpose of this paper is to discover a method to reduce risk and increase investment returns. By analyzing the mass volume of Tehran stock market data as a case study, and finding the relationships between the data and the discovery of their hidden information that has a significant impact on investors' decisions; an algorithm was designed. Moreover, the data from the automobile industry and oil products and the index of various industries were utilized from 2018 to 2022, and modeling was done by twenty technical indicators. The results of this research showed that mentioned model has a significant performance in identifying and predicting the sales signals issued at the maximum points and the prediction is done with acceptable accuracy. Portfolio management and capital supply companies can use this trading algorithm to make decisions regarding the sale, purchase or holding of securities. Manuscript profile -
Open Access Article
527 - مقایسه مدل های شبکه عصبی با مدل سری زمانی باکس- جنکینز در پیش بینی شاخص کل قیمت سهام بورس اوراق بهادار تهران
جلال حقیقت منفرد محمود احمدعلینژاد سارا متقالچی -
Open Access Article
528 - ارائه مدلی جهت پیشبینی ورشکستگی شرکتهای پذیرفته شده در بورس اوراق بهادار تهران با استفاده از سیستم استنتاج فازی عصبی انطباق پذیر (ANFIS)
حمیدرضا وکیلی فرد نازنین پیله وری سیده سمانه زیدی -
Open Access Article
529 - بررسی ناپایداری سود و قابلیت پیش بینی سود آتی در شرکتهای پذیرفته شده در بورس اوراق بهادارتهران
هاشم ولیپور محمد آشوب -
Open Access Article
530 - The Impact of Earning Quality on Excess Returns with Regard to Momentum
Vahid Bekhradinasab Fatemeh ZholanezhadTehran Stock Exchange has not lived and somewhat inefficient. Mechanisms and rules governing this market is still not implemented in such a way that the quality of data and information provided by member companies to deliver optimal.and suffered not because of pricing e MoreTehran Stock Exchange has not lived and somewhat inefficient. Mechanisms and rules governing this market is still not implemented in such a way that the quality of data and information provided by member companies to deliver optimal.and suffered not because of pricing errors. Probably the most attention of users of financial statements, the income statement is focused on the lowest row. In the eyes of most, profit accounting tool for making logical decisions In general indicates that measures the quality of earnings on excess stock returns based on Fama and French three-factor model, taking into account the trend of stock prices of listed companies on Tehran Stock Exchange, is impressive. In this study of four indicators to measure earnings quality, earnings stability, predictability of earnings, accruals quality and smoothing was used as the four hypothesis that the effect of these measures on additional efficiency gains from the difference between the real Return expected return achieved was measured and the results of the test showed that the hypothesis were accepted theories, the literature cited in the literature and theoretical framework also matched. Manuscript profile -
Open Access Article
531 - Corporates Manner and Comparing its Prediction Accuracy with Decision Tree and Bayes Models
zohre arefmanesh vahid zare mehrjardi Alireza Mohammadi nodooshanThe main objective of this study is to design corporate financial distress prediction models for the following three industries basic metals, non-metallic minerals and machinery and equipment, using the bagging model. Moreover, the prediction accuracies of the designed MoreThe main objective of this study is to design corporate financial distress prediction models for the following three industries basic metals, non-metallic minerals and machinery and equipment, using the bagging model. Moreover, the prediction accuracies of the designed models are compared to the bayes and decision tree models. Aimed Statistical population of this research includes all the corporations of each of the industries. The financial distress criterion employed in this research is the criteria of article 141 in commercial code and the timeline of the research is from 2001 to 2016. The results shows that, comparing to the base models (i.e. decision tree and bayes), the bagging model has a better prediction accuracy average. Moreover, based on the obtained results, it can be concluded that the bagging, decision tree and bayes models are qualified models for the corporate bankruptcy prediction Manuscript profile -
Open Access Article
532 - Applying hybrid algorithm of fuzzy time series for stock price forecasting and comparing them with calculating stock price achieved by golden ratio technique for Tehran Stock Exchange companies
Negar Aghaeefar Mohammad Ebrahim Mohammad PourzranadiThe especial importance of capital market in countries is undeniable in economic development via effective capital conduct and optimum resources allocation. Investment in capital market requires decision making in new stock exchanges, and accessing information in the ca MoreThe especial importance of capital market in countries is undeniable in economic development via effective capital conduct and optimum resources allocation. Investment in capital market requires decision making in new stock exchanges, and accessing information in the case of future status of capital market. Forecasting stock market price has always been a challenging task, since it is affected by many economic and non-economic factors and variables; therefore, selecting the best and the most efficient forecasting model is tough and essential. For this forecasting, we need a computing model with systematic method that can be estimated in this research. The attribution of this test considering one of the stock exchange industries is forecasting prices and contrasting them with calculated price achieved by Golden ratio algorithm. Banking industry is selected and all of listed in bourse and farabourse banks are reviewd that the results of one of them is presented in this article. Time-series and Fuzzy logic models are used for rationalization. Fuzzy time-series models have been utilized to make reasonably accurate prediction in the area of stock price movements.The mentioned combined method are run on the average of weekly prices of Tehran Stock Exchange. In this research stock trade for investors with calculated relations are displayed. Manuscript profile -
Open Access Article
533 - مقایسه عملکرد مدلهای رگرسیونی ARIMA وشبکه عصبی باالگوریتم ژنتیک (GMDH) درپیش بینی قیمت نفت خام ایران
عباسعلی ابونوری ناهید خدادادی -
Open Access Article
534 - طراحی مدل پیش بینی ورشکستگی شرکت ها به وسیله شبکه های عصبی فازی (مطالعه موردی:شرکت های بورس اوراق بهادار تهران)
مریم ظهری محمدعلی افشارکاظمی -
Open Access Article
535 - یش بینی ورشکستگی شرکتها با استفاده از مدل لاجیت
سیدعلی نبوی چاشمی موسی احمدی صادق مهدوی فرح آبادی -
Open Access Article
536 - Providing a model for predicting stock prices using ultra-innovative neural networks
Seyyed Hosein Miralavi zahra pourzamaniDue to the complexity of the stock market and the high volume of processable information, often using a simple system to predict cannot release appropriate results. Therefore, researchers have been trying to provide a system with less complexity and more efficiency and MoreDue to the complexity of the stock market and the high volume of processable information, often using a simple system to predict cannot release appropriate results. Therefore, researchers have been trying to provide a system with less complexity and more efficiency and accuracy using hybrid models. nowadays various patters are used including statistical technique (discriminate analysis , logistic , analysis factors) and artificial intelligent techniques ( neural networks(NN) , decision trees , case based reasoning , genetic algorithm , rough sets , support vector machine , fuzzy logic ) and the combination of these two technique for predicating stock prices. For most predictive models, the system uses only one indicator to predict, but in the proposed model in this study, a two-level system of multilayered perceptron neural networks is presented which uses several indicators to predict. To do this, required information of Tehran Stock Exchange price indicators, for fiscal years 2012 - 2017 was collected. We also used the Grasshopper Optimization Algorithm to select the best samples for better nerve network training and thus to improve the results. The results show that the proposed model can operate with lower prediction error than other models. Manuscript profile -
Open Access Article
537 - پیش بینی بازده شاخص بورس اوراق بهادار با استفاده از مدلهای شبکه ها عصبی مصنوعی شعاع پایه
رضا تهرانی سعید مرادپور -
Open Access Article
538 - کاربردالگوریتم ژنتیک خطی و غیر خطی در بهبود قدرت پیشبینی
زهرا پورزمانی -
Open Access Article
539 - مدلسازی پیشبینی قیمت ارز با استفاده از شبکههای عصبی
مهدی غفاری راحله یوسفی -
Open Access Article
540 - اندازه گیری خطای پیش بینی شاخص کل بورس تهران با استفاده از روشهای سری زمانی فازی مرتبه چندگانه و آرما
ابراهیم عباسی محسن دستپاک -
Open Access Article
541 - Risk and Return Properties of Portfolios Based on Directional Forecasts
Vahid RooholelmIn this study, a formula is de rived for the period specific beta (market risk) for a portfolio of financial assets that has been formed on the basis of directional forecasts. This is an important contribution to the literature since measuring the risk of an actively ma MoreIn this study, a formula is de rived for the period specific beta (market risk) for a portfolio of financial assets that has been formed on the basis of directional forecasts. This is an important contribution to the literature since measuring the risk of an actively managed portfolio is problematic due to the fact that managers may change fund risk conditional on market expectations. The period- specific nature of the measure is a significant advantage since historical fund re turns are not required and the beta is not influenced by prior fund returns’ deviations from the bench mark. The methodology employed allows for the development of a time series of fund betas that permits investigation into a number of important Empirical issues. This study is also of practical interest from the perspective of risk management and for both portfolio performance and attribution. Finally, there are many active strategies based on directional forecasts and the approach used here en com passes a significant proportion of these. The author of this article used of consultation and guidance of Rahnama Roodposhti Fereidoun, Professor and A member of the science team Islamic Azad University, Science and Research Branch ,Tehran, and thankses a lot of him. Manuscript profile -
Open Access Article
542 - Smart Buying and Selling System Design Based on a Model Consisting of a Support Vector Machine Algorithm and Theory of Trend Channel
Shapoor Mohammadi Seyyed Ali Mousavi Sarhadi Mohammad NooribakhshPredicting future prices and consequently higher returns in financial markets has been one of the most important issues. In this study, the design of intelligent systems to buy and sell based on a complex model of support vector machine algorithm and theory of tre MorePredicting future prices and consequently higher returns in financial markets has been one of the most important issues. In this study, the design of intelligent systems to buy and sell based on a complex model of support vector machine algorithm and theory of trend channel been discussed. To achieve the aim of this object, this study was performed in four main steps. In the first phase, range or limits of trend channel at different time intervals were extracted and these limits in the second phase of the experiment was predicted by the algorithm and Support Vector Machine.In the second phase in the range of channel which been predicted in period of experiment, sales strategy was defined and implemented. And in the third stage, returns from system designed with efficiency resulting from the use of buy and hold strategies were compared. In all selection criteria as a sample, Intelligent system performance based on the model of combined sales and support vector machine algorithm and theory of trend channel was better than the performance of buy and hold strategy Manuscript profile -
Open Access Article
543 - A Markov regime-switching model for crude-oil market fluctuations
mohammadreza Rostami maryam naghavipour maryam MoghaddasbayatAccording to the findings of financial econometric researches, oil prices as one of the most important macroeconomic variables affect financial markets and economies of oil exporting countries. In this study, the price of OPEC oil basket has been used with daily frequen MoreAccording to the findings of financial econometric researches, oil prices as one of the most important macroeconomic variables affect financial markets and economies of oil exporting countries. In this study, the price of OPEC oil basket has been used with daily frequency. The period under review is from August 3, 2013 to December 26, 2016. The course includes various developments such as unrest and war in the Middle East, a sharp and unexpected decline in oil prices for reasons such as a decline in demand, an agreement 27, and the agreement of OPEC members to reduce oil production in order to increase oil prices, is located. Initial studies indicate cluster fluctuations, ie, independent and uniform distribution characteristics and variance consistency. The Breusch Godfrey test confirms the effects of ARCH and GARCH. Also, a generalized test with the estimation of kernel density based on the Monte Carlo rule indicates Parson’s weight on the effects of ARCH in the variable. The results of the study of oil price fluctuations using the MS-GARCH model of single and multiple regimes indicate that the three regimes model is suitable for explaining the behavior of the variable in the reviewed period. Manuscript profile -
Open Access Article
544 - کاربرد شبکه عصبی- فازی انطباقی در پیشبینی قیمت سهام شرکت ایرانخودرو
ابراهیم عباسی امیر ابوئی مهریزی -
Open Access Article
545 - Mathematical model design for predicting bankruptcy of companies accepted in the Tehran Stock Exchange
Reza Pirayesh Hassan Dadashi Arani Mohammadreza BarzegarIn this research, five major bankruptcy predictions model to study and among the components of the five models, redesigned bankruptcy prediction is provided that consists of eight variables. The main issue in this research is that by examining the financial statements o MoreIn this research, five major bankruptcy predictions model to study and among the components of the five models, redesigned bankruptcy prediction is provided that consists of eight variables. The main issue in this research is that by examining the financial statements of listed companies in Tehran Stock Exchange we can offer a model to predict corporate bankruptcy. In order to design data from two groups of companies accepted in the Tehran Stock Exchange use the first group consists companies surveyed non-bankrupt company and second group included bankrupt company. The study period financial statements of exchange data during the years have been 2005 to 2014. The study results in relation to the ability to predict model reflects the fact that the model could be two years before the bankruptcy of companies provide accurate predictions about the crisis and bankruptcy. The results show that the predictive power of the model for one year before bankruptcy 91% and two years before the bankruptcy 83%. Manuscript profile -
Open Access Article
546 - Comparing Different Feature Selection Methods in Financial Distress Prediction of the Firms Listed in Tehran Stock Exchange
Mohammad Namazi Mostafa Kazemnezhad M. Mahdi NematollahiResearch in financial distress and bankruptcy emphasize the design of more sophisticated classifiers, and less feature (variables) selection and their appropriate methods. In this regard, the purpose of this study is to compare performance of different feature selection MoreResearch in financial distress and bankruptcy emphasize the design of more sophisticated classifiers, and less feature (variables) selection and their appropriate methods. In this regard, the purpose of this study is to compare performance of different feature selection methods in financial distress prediction of the companies listed on Tehran Stock Exchange (TSE). In this regard, we investigated and compared five feature selection methods, including t-test, stepwise regression, factor analysis, relief, wrapper subset selection and RFE-SVM feature selection. To obtain comparable experimental results (reliable comparison), three different classifiers (including neural networks, support vector machine and AdaBoost) were used in this study. In overall, the experimental results confirmed the usefulness of variable selection methods and significant difference among level (amount) of different methods performance. In other words, the application of the feature selection methods increases the mean of accuracy, and reduces the occurrence of type I and type II errors. Furthermore, the results indicated that wrapper subset selection method outperforms the other feature selection methods. Manuscript profile -
Open Access Article
547 - Stock price prediction based on LM-BP neural network and over-point estimation by counting time intervals: Evidence from the Stock Exchange
Mohammadreza Vatanparast masoud asadi Shaban Mohammadi abbas babaeiIn this study, to determine the stock price forecasting method, a LM-BP neural network was presented based on time series with respect to open price, highest price, lowest price, package price and volume of transactions. In the present study 315 days of stock prices wer MoreIn this study, to determine the stock price forecasting method, a LM-BP neural network was presented based on time series with respect to open price, highest price, lowest price, package price and volume of transactions. In the present study 315 days of stock prices were chosen to create 10 samples and the test set includes stock prices from day 316 to day 320 and used the LM-BP neural network. In this research, the determination of the critical point of excess, asymmetry and counting of intervals were investigated. The curve MRE2-MRE1 was plotted and the precision related to the best prediction of the BP neural network was estimated based on several independent replicas. The post-test was performed using a Kupiec Test and a Christopherson test. The results showed that stock price prediction based on the LM-BP neural network and over-point estimation by counting the intervals resulted in better results than the existing methods. Manuscript profile -
Open Access Article
548 - Proposition of a model For Forecasting Value at Risk in One Step Ahead
ehsan Mohammadian Amiri S. Babak Ebrahimi maryam Nezhad AfrasiabiRisk forecasting for future periods plays an important role in making the right decisions of managers and financial activists to invest in companies and institutions. On the other hand wrong decisions of commercial managers can have undesirable consequences for their or MoreRisk forecasting for future periods plays an important role in making the right decisions of managers and financial activists to invest in companies and institutions. On the other hand wrong decisions of commercial managers can have undesirable consequences for their organizations. Therefore the most important issues for investors is forecasting risk in future periods. The importance of this issue was caused us to forecast Value at Risk (VaR) in one step ahead by using the exponential smoothing family for two normal and t-student distributions with confidence levels of 95%, 97.5% and also 99% in this research. Previously the classic method is commonly used to forecast future periods of VaR, but in this research the family of exponential smoothing models is used, which process data by considering trend and doing so online monitoring. In order to validate the model, the proposed model has been compared with the classic method by using backtesting. The results confirms the more accurate forecasting of proposed method in normal distribution with confidence levels of 97.5%, and 99% and also in t-student distribution with confidence levels of 97.5%, 99%. Manuscript profile -
Open Access Article
549 - Checking the accuracy of learning machines in predicting stock returns using the Rough set model, Nearest neighbor and decision tree.
mohammad reza karimi pouya mehrdad ghanbari babak jamshidinavid mansoor esmaeilpourPrediction is an essential component of short and medium term planning in any business. A precise prediction can be effective in generating returns, managing cash flows, and allocating resources, enabling an investor to estimate, within a given time frame, its business MorePrediction is an essential component of short and medium term planning in any business. A precise prediction can be effective in generating returns, managing cash flows, and allocating resources, enabling an investor to estimate, within a given time frame, its business revenue and its returns. Researchers have the idea to set aside old methods, which takes expense and time, and implement new methods such as the use of learning machines. This research is of the type of research, analytical-empirical, in terms of research design, post-event, in terms of purpose, applied, in terms of implementation logic, deductive and in terms of time, longitudinal and prospective type. In this research, the algorithm model of the nearest neighbor, the Rough method and the decision tree are used to improve predictive power, cost reduction, and time prediction of stock returns. For this purpose, a sample of 113 listed companies in the Tehran Stock Exchange during a 10-year period (2006-2015) was selected from the companies listed in the Tehran Stock Exchange. The results of the research showed that all the hypotheses of this research are based on a difference in the accuracy of estimating these models in the prediction of the three dependent variables. Manuscript profile -
Open Access Article
550 - Modeling and Forecasting Evaluation of Different Models of Short-Term Memory, Long-Term Memory, Markov Switching and Hyperbolic GARCH in Forecasting OPEC Crude Oil Price Volatility
mahmood mohammadi alamuti Mohammadreza Haddadi Younes NademiPredictability in financial markets is very complex, and the reasons for this complexity can be summarized as non-standard data, nonlinear data flow, and large variations in data. Determining the proper pattern for forecasting volatility can play a significant role in d MorePredictability in financial markets is very complex, and the reasons for this complexity can be summarized as non-standard data, nonlinear data flow, and large variations in data. Determining the proper pattern for forecasting volatility can play a significant role in decision making. In the old econometric models it is assumed that the component of error constant during the sample period. But in many financial time series it is observed that during periods of volatility is very sever. Under these conditions, the assumption of the exictence of the equivalence of variance is no longer reasonable. In the present paper, the GARCH, IGARCH, EGARCH, GJR-GARCH, FIEGARCH, HYGARCH, and MRS-GARCH two-regime models were evaluated in prediction of OPEC crude oil price volatility during 2010-2016 based on their RMSE error criterion. The results of this evaluation show the superiority of the Markov Switching GARCH Model on the 5 and 22-day horizons. Also, the long-term FIEGARCH memory model in predicting horizons of 1 and 10 days has better performance in predicting oil price volatilities than other competing models. Manuscript profile -
Open Access Article
551 - Choosing an optimal Model for Explaining & Forecasting the Volatility of Iranian Gold Price Returns: a Comparison of GARCH, IGARCH & FIGARCH Models
Mahdi ShahraziThis paper compares three models of the GARCH family to investigate the volatility dynamics of gold Price returns. Nowadays, GARCH-type models have been extensively used in modeling the volatility process of various asset price returns. Gold plays a critical role as a h MoreThis paper compares three models of the GARCH family to investigate the volatility dynamics of gold Price returns. Nowadays, GARCH-type models have been extensively used in modeling the volatility process of various asset price returns. Gold plays a critical role as a hedge against adverse market conditions. An accurate understanding about the gold volatility is important for the financial assets pricing, risk management, portfolio selection hedging strategies and value-at-risk policies. In this study, we use Iranian gold returns data from March 25, 2003 to December 25, 2015 and employ the GARCH(1,1), IGARCH(1,1) and FIGARCH(1,d,1) specifications. The research findings show that the FIGARCH is the best model to capture dependence in the conditional variance of the gold returns. Moreover, we examine the long memory behavior in the volatility of gold returns. According to the estimation results, the long memory parameter is positive and statistically significant. Consequently, long memory is an important characteristic of the gold volatility returns and should be taken into consideration in investment decisions. Also, the out-of-sample evaluation criteria (MAE, RMSE and TIC) select the FIGARCH(1,d,1) as the best forecasting model of gold volatility. Manuscript profile -
Open Access Article
552 - The use of Firefly Algorithm and Bayesian Regulation technique of optimized Artificial Neural Network to predict stock price in Iran Stock Market
seyyed alireza mosavi Afsaneh GholamiPredicting the future stock price has always been considered as an important issue by both buyers and sellers. Hence, Artificial Neural Network (ANN) was used in this study to develop a model pertaining to artificial intelligence in order to predict stock price in Iran MorePredicting the future stock price has always been considered as an important issue by both buyers and sellers. Hence, Artificial Neural Network (ANN) was used in this study to develop a model pertaining to artificial intelligence in order to predict stock price in Iran Stock Market. Since artificial neural networks should consist of the best network topology to achieve the highest performance, Firefly Algorithm (FA), a meta-heuristic Algorithm, was used to find the optimal structure of network. Finally, Bayesian regulation technique, rather than the conventional teaching techniques, was applied to maintain the more generalized network. In general, Data from three big companies: Iran Khodro Company, Shiraz Petrochemical Company, and Isfahan Steel Companywere gathered in span of three years. This paper profited from some parameters, including high price, low price, the opening price, closing price, EMA(5) ،EMA(10) ،RSI ،William R% ،Stochastic k% ،Stochastic D% و ،ROCas network inputs and benefited from the closing stock price in the next days as the neural network as well. After developing a model associated with each company, some parameters such as the root-mean-square error (RMSE), Standard Deviation of error(SD), Absolute average relative deviation (AARD), the regression coefficient (R2) as well as the graphical analysis of relative deviation have been used to examine the accuracy of the developed network. The outcomes of the analysis of the developed neural networks revealed that the mentioned models with great accuracy are able to predict stock price in the subsequent day for the corporations mentioned above. Manuscript profile -
Open Access Article
553 - Predicting the Direction of Stock Market Prices Using Random Forest
elham gholamian sayyed mohammad reza davoodiStock market activists are the acquiring and using methods to predict future stock prices, increasing their capital gains. Therefore, it seems necessary that appropriate, correct, and scientific principles are used to determine the future price of the stock of investor MoreStock market activists are the acquiring and using methods to predict future stock prices, increasing their capital gains. Therefore, it seems necessary that appropriate, correct, and scientific principles are used to determine the future price of the stock of investor stock options.stock price prediction is an important part of investment, and in most cases it is the field of research for researchers, because it ultimately leads to the choice of appropriate investment. Different methods have now been developed to achieve this goal. Have been introduced that are often statistical methods and artificial intelligence. In this research, using a randomized approach approach that is among artificial intelligence classification methods, along with technical indicators that include: power index Relative Price, Stochastic, Equilibrium Balance, Williams R%, Daily Returns, and Mac.d Series Markets, are looking for stock price trends. This model is compared with logistic regression method and completely randomized method (dice throw). The results of the research on daily data of Tehran Stock Exchange Index from 1393 to 1395 indicate that the accuracy of the proposed method in estimating market trend is 64%, which is more than two methods of logistic regressionand completely randomized method of accuracy Has a higher rate. Manuscript profile -
Open Access Article
554 - Tehran Stock Exchange Overal Index Prediction using Combined Approach of Metaheuristic Algorithms, Artificial Intelligence and Parametric Mother Wavelet
Alireza Saranj Madjid Ghods reza tehraniUnderstanding and the investigating the behavior of stock prices, has always been one of the major topics of interest to the investors and finance scholars. In recent years, various models for prediction using neural network and hybrid models have been proposed which ha MoreUnderstanding and the investigating the behavior of stock prices, has always been one of the major topics of interest to the investors and finance scholars. In recent years, various models for prediction using neural network and hybrid models have been proposed which have a better performance than the traditional models. Here a hybrid model of neural network and wavelet transform is proposed in which genetic algorithm has been used to improve the performance of wavelet transform in optimizing the wavelet function. Daily stock exchange rates of TSE from April 21, 2012 to April 19, 2017 are used to develop a prediction model. The results show that it is possible to find a wavelet basis, which will be appropriate to the intrinsic characteristics of time series for prediction and the prediction error in this model is reduced comparing to the neural network and hybrid neural network and wavelet models. Manuscript profile -
Open Access Article
555 - Forecasting the exchange rate of euro to dollar with the artificial neural network technique
shafagh sharif moghadam seyyed Zabihollah HashemiExchange rate prediction is an important economic variable of interest to the economic actors. Technical approach is one of the commonly used approaches to forecasting, which uses the past behavior of the exchange rate for prediction. However, given the chaotic and non- MoreExchange rate prediction is an important economic variable of interest to the economic actors. Technical approach is one of the commonly used approaches to forecasting, which uses the past behavior of the exchange rate for prediction. However, given the chaotic and non-linear structure of financial markets, the market forecasting cannot be done using a certain and simple method obtained by combining different technical tools and more sophisticated methods are required. In recent decades, neural networks have been employed as one of the most widely used methods in classification, pattern recognition and prediction of complex time series. In this research, a multilevel neural network model was provided to predict the euro-dollar exchange rate, which predicts the price on the next day with an appropriate accuracy by utilizing the data and variables derived from the technical analysis. The results demonstrated the proper function of this method versus other conventional methods of technical analysis and neural network. Manuscript profile -
Open Access Article
556 - The Study of the effect of Internal Audit Function Quality on Management Earnings Forecasts Accuracy
Yassaman Khalili davood Hassanpour ابولفضل مومنی یانسریManagement forecasts are disclosures made by companies to communicate information about their future performance to shareholders. These disclosures are voluntary and are intended to reduce information asymmetry between management and shareholders. Incorrect forecasts ca MoreManagement forecasts are disclosures made by companies to communicate information about their future performance to shareholders. These disclosures are voluntary and are intended to reduce information asymmetry between management and shareholders. Incorrect forecasts can be very costly for managers and question the credibility of managers and show managerial incompetence. The quality of the internal audit function reduces the likelihood of erroneous, biased, or incomplete information in management reports, which managers use to improve their earnings forecasts. Therefore, in the present study, the effect of internal audit function quality on management earnings forecasts accuracy was experimentally tested. To test the research hypothesis, the financial data of the firms listed in Tehran Stocks Exchange during the time period 2018-2022 was used, so that after applying the restrictions in this research, the final sample consisting of 136 firms was selected. After measuring the research variables, multivariate regression analysis based on panel data estimation was used to test the research hypothesis, and the results of the statistical tests showed that there is a positive and significant relationship between internal audit function quality and management earnings forecasts accuracy. Manuscript profile -
Open Access Article
557 - The Impact of Accounting Information Quality and Monetary Policy on Bankruptcy Prediction
Mohammad Hossein Setyesh milad rahimiAbstractThis study has investigated the effect of the accounting information quality and monetary policy on bankruptcy prediction. For this purpose, a sample of 135 companies was selected from the admitted companies in the stock exchange. In order to collect the needed MoreAbstractThis study has investigated the effect of the accounting information quality and monetary policy on bankruptcy prediction. For this purpose, a sample of 135 companies was selected from the admitted companies in the stock exchange. In order to collect the needed data to calculate variables in the research, Rahvardnovin database, Tehran Stock Exchange Organization database and Central Bank database were used. Eviews software and fixed effects panel data regression model have been used to analyze the collected data. This study is useful for financial analysts, managers, accountants and policy makers in order to evaluate the financial position and predict financial bankruptcy of companies. The results of the hypothesis test show that all three hypotheses are not rejected and indicate that the accounting information quality in interaction with monetary policy has a positive and significant effect on bankruptcy prediction. The estimated coefficient of the accounting information quality in the interaction with monetary policy on predicting premature bankruptcy is lower than the coefficients of the variables accounting information quality and monetary policy on predicting premature bankruptcy, and this shows that the interaction of the accounting information quality and monetary policy has a moderating role on It has predicted premature bankruptcy. Manuscript profile -
Open Access Article
558 - stock return prediction models; Estimating the distribution of total market returns and its fluctuations based on the Laplace distribution
Masoumeh Mohammadi Ledari Iman DadashiAbstractIn most return forecasting models, the return of the total market is used as one of the factors affecting the return of securities. In most of these models, such as the pricing model of capital assets and Black-Scholes, the data distribution is assumed to be nor MoreAbstractIn most return forecasting models, the return of the total market is used as one of the factors affecting the return of securities. In most of these models, such as the pricing model of capital assets and Black-Scholes, the data distribution is assumed to be normal. This is while the distribution of the total return is not necessarily normal and often has a significant difference from the normal distribution. If such a hypothesis is confirmed, the expected return predicted by these models will not be very effective in financial decisions. The purpose of this research is to model the total return of Tehran Stock Exchange based on the Laplace distribution and examine the dependence of the total return fluctuations on the desired distribution. In order to examine the distribution of the total daily return and its weekly fluctuations, data related to a 15-year period between 1387 and 1401 and R statistical software were used. The data analysis showed that the total daily return followed the Laplace distribution and the weekly fluctuations of the total return followed the distribution obtained based on the Laplace distribution. These findings make the use of models with the assumption of normality of total return to predict stock returns in Tehran Stock Exchange a major challenge and are a clear proof of the ineffectiveness of these models. . Manuscript profile -
Open Access Article
559 - Peer Companies Performance and Earnings Management: The Effect of Capital Market Pressure Peer Companies Performance and Earnings Management: The Effect of Capital Market Pressure
reza kordestani سیده آمنه جعفری سوق Abstract Financial analysts and investors use the performance of peer firms for valuation and investment decisions. Since managers know that their performance is compared to peer’s firms, they have enough incentive to earnings manipulation. Therefore, the More Abstract Financial analysts and investors use the performance of peer firms for valuation and investment decisions. Since managers know that their performance is compared to peer’s firms, they have enough incentive to earnings manipulation. Therefore, the purpose of the present research is to investigate the relationship performance of peer firms on earnings management. Based on analysis of archival data of 114 firms listed in TSE, the findings show that there is a positive and significant relationship between performance of peer firms and earnings management. That is, the high performance of peer firms leads to increased discretionary accruals. In addition, change in earnings forecast per manager share has a positive and significant relationship with peer firm performance. Also, there is a significant relationship between the criterion of earnings forecast and performance of peer firms. Therefore, managers in response to the performance of peer firms and under the capital market pressure, manipulation of accounting earnings. This study focused more on the impact of peer firms and their performance on the quality of financial reporting. In addition, earnings management studies in the scope of motivation is broaden. Manuscript profile -
Open Access Article
560 - The mediating role of metacognitive awareness in the relationship between school effectiveness and students' academic optimism
mahsa mahmoudi mashaii maedeh ebrahimi zahed zahra sadri mohammadreza zaeri behroz abbas najafipour tabestanaghThe aim of the present study was to determine the mediating role of metacognitive awareness in the relationship between school effectiveness and students' academic optimism. The method of the research was descriptive correlational. The statistical population included al MoreThe aim of the present study was to determine the mediating role of metacognitive awareness in the relationship between school effectiveness and students' academic optimism. The method of the research was descriptive correlational. The statistical population included all students of the 11th grade of the second period of secondary school in Zanjan in the academic year of 2022-2023 totaling to 5600 people, of which 300 people were recruited based on Morgan’s table after consulting with university professors. The research tools for data collection were three school effectiveness questionnaires of Hoy (2009), Techanen-Moran (2013) academic optimism and Mokhtari and Richard (2002) metacognitive self-awareness. Structural models with partial least squares approach were used for data analysis. The results of the analysis showed that the direct effects of school effectiveness on academic optimism (t=4.96, p=0.000) and metacognitive self-awareness (t=4.38, p=0.02), and metacognitive awareness on academic optimism (t=9.96, p = 0.000) were significant. Also, the indirect effect of school effectiveness on academic optimism with the mediation of metacognitive self-awareness was also significant (t=9.37, p=0.001). Finally, the proposed model has a good fit. Manuscript profile -
Open Access Article
561 - Predicting the success of the investment projects of Aras and Maku commercial-industrial free zones and Salmas special economic zone using perceptron multilayer neural network technique
morteza shokrzadeh mojtaba shokrzadehTo analyze the data of this research descriptive statistics and inferential statistics were used and experts selection software, MATLAB SPSS and PLS software were employed.Using theoretical foundations and libraries, six effective factors and variables predicting the su MoreTo analyze the data of this research descriptive statistics and inferential statistics were used and experts selection software, MATLAB SPSS and PLS software were employed.Using theoretical foundations and libraries, six effective factors and variables predicting the success or failure of Investment projects in the free and special economic zones of the country were identified. After describing the variables and testing the normality,using the PLS software, a confirmatory factor analysis of the variables was carried out, in which all of the factors had a good confirmatory factor analysis and all the questions were approvedThen, using linear regression and ANOVA, the effect of each of the factors on the success or failure of investment projects was investigated, and the results of this test showed confirmation of the impact of each of the factors, and then the results of the hierarchical analysis indicated this was the first rank of product and service, followed by the second-rank ,that is geographical considerations, and the characteristics of the investor's psychology, the third rank, the product market characteristics, the fourth rank, the investor's ability to rank fifth, and financial considerations ,also, earned the last rank. Considering this prioritization, the neural network used in this research contained data from 6 variables as an input variable, with two intermediate layers with 30 nodes in the first layer, and three nodes in the second layer,which had one outlet. The results indicated that the neural network model had the power to predict the success of the investment projects to1.2%of the error Manuscript profile -
Open Access Article
562 - Prediction of growth stages of soybean cultivars and lines using climatologic parameters of photoperiod and temperature in karaj region
Sharareh Nasre Esfahani Jahanfar Daneshian Ebrahim Pazira Amir hosein Shirani RadSoybean development Reproductive stage werepredicted by climatic parameters as daylength and temperature . Therefore ,fifteen soybean lines and cultivars as name as Williams, Zane, M4, M12, S.R.F, Miandoab,A3935, A3237, L17, Union, Grangelb, Clark, Tns95,Elf, Calland we MoreSoybean development Reproductive stage werepredicted by climatic parameters as daylength and temperature . Therefore ,fifteen soybean lines and cultivars as name as Williams, Zane, M4, M12, S.R.F, Miandoab,A3935, A3237, L17, Union, Grangelb, Clark, Tns95,Elf, Calland were studied in four planting dates. Soybean genotipes were usedin a RCBD in each planting dates . Daylength and temperature effect wereevaluated by planting dates levels. Flowering occurance and developmentReproductive stage duration were fitted growth degree days, photoperiod andphotothermal units in a Multiple Regression Method. The results indicated thatphotoperiod had significant effect on Maturity in all of lines and cultivars.But photothermal had positive significant effect in Williams. Therefore Itcaused to delay in Maturity if It was increased. Photothermal was calculatedfrom growth degree days by photoperiod in each days. But the photoperiod wasmore effective than gdd in time of Maturity. Growth degree days affected ontime of Maturity by photothermal and caused to promote it. Reproductivedevelopment duration of Elf was affected by gdd Manuscript profile -
Open Access Article
563 - Forecasting Stocks in the Financial Market by Using GA-SVM Hybrid Algorithm
Omid Mahdi Ebadati Mohammad Ali Jafari Nasim DavoodifarThe purpose of this paper is to predict stock prices using Hybrid GA-SVM Algorithm. Predicting time series such as stock price forecasting is one of the most important issues in financial field. In real life, identifying time series movements in stock price indices is v MoreThe purpose of this paper is to predict stock prices using Hybrid GA-SVM Algorithm. Predicting time series such as stock price forecasting is one of the most important issues in financial field. In real life, identifying time series movements in stock price indices is very complex. Therefore, the use of a classical model alone cannot accurately predict stock price indices. Hence, by using combined methods, uncertainty in forecasting can be reduced. In stock price forecasting in financial sector, more than 100 indicators have been created to understand stock market behavior, so, identifying the appropriate indicators is a challenging problem. One of the techniques that has recently been studied for serial forecasting is support regression Vector (SVR) or machine support vector (SVM). This study uses the GA-SVM hybrid algorithm to predict the stock price index. Experimental results show that Hybrid GA-SVM Algorithm provides a more appropriate and promising alternative to stock market forecasting. Manuscript profile -
Open Access Article
564 - The Mediator role of Information Asymmetry in Imperfect Competition Market on the relation between Earnings Forecast Bias & Idiosyncratic Risk derived from Capital Assets Pricing Model
Mohammad Hassani Sanaz MoradiTheoretically, firms should reduce information risks to provide a transparent environment for different groups in capital market to make decisions. Therefore, identifying potential risk factors is important. This paper investigated the impact of earnings forecast bias a MoreTheoretically, firms should reduce information risks to provide a transparent environment for different groups in capital market to make decisions. Therefore, identifying potential risk factors is important. This paper investigated the impact of earnings forecast bias and information asymmetry in imperfect competition market on the idiosyncratic risk. It is used the standard deviation of residuals extracted from capital asset pricing model to measure the idiosyncratic risk. Earnings forecast bias is measured based on the absolute value of difference between actual value and forecasted value of earnings per share scaled by the beginning stock price. In addition, information asymmetry is assessed based on the stock price bid-ask spread. Using filtering method, 147 firms listed in Tehran Securities & Exchange during 2013 to 2018 selected as research population. Research hypotheses analyzed through multivariate regression models. Research results showed that more earnings forecast bias lead to increase the idiosyncratic risk. In addition, high level of information asymmetry caused to increase the idiosyncratic risk. Also information asymmetry lead to strengthen the positive relation between earnings forecast bias and idiosyncratic risk. As a whole, firms with high level of earnings forecast bias & information asymmetry as inverse proxies of information quality which have worse information environment have more idiosyncratic risk. Manuscript profile -
Open Access Article
565 - The effect of information environment on the relationship between consistency in book-tax differences and analysts’ earnings forecasts
Mohammad Salari Abarghuoi Nasim ShahmoradiPurpose: Predicting accounting earnings and its changes as an economic event has long been of interest to financial analysts and researchers.The purpose of this study is to investigate the effect of information environment on the relationship between consistency in book MorePurpose: Predicting accounting earnings and its changes as an economic event has long been of interest to financial analysts and researchers.The purpose of this study is to investigate the effect of information environment on the relationship between consistency in book-tax differences and the accuracy of analysts’ of corporate earnings forecasts.Methodology: In this study, following the research of Choi, Hu and Khondkar (2020), the information environment and the quality of analysts' forecasts in two dimensions of predictive and prediction accuracy, consistency in book-tax differences in both temporary and Permanently dimensions were calculated and regression models were tested using the Generalized Torque Model (GMM). The selected sample consisted of 69 companies listed on the Tehran Stock Exchange between 2011 and 2020.Findings: : Generally findings indicate that consistency in book-tax differences has affected the prediction accuracy of analysts' forecasts. In a way, temporary consistency has led to an increase and permanent consistency has led to a decrease in analysts' forecast prediction accuracy. In addition, consistency in book-tax differences has also affected the analysts' forecasts predictive accuracy, which has been increasing for temporary consistency and decreasing for permanent predictive consistency.The information environment has also affected both the predictive and prediction accuracy of the analysts' forecasts.Originality / Value: The obtained results have led to the expansion of the theoretical foundations in relation to the factors affecting the quality of analysts' forecasts, in two aspects: accuracy and usefulness of forecasts. And besides that, it is useful for company managers in adopting the necessary policies to create a suitable information environment. The mentioned relationships are measured bilaterally and include temporary and permanent differences in the taxes paid by companies. which provides useful information in this field for standard setters and legislators. Manuscript profile -
Open Access Article
566 - Systematic review of bankruptcy prediction models
Jaber Zahmatkesh Akram Taftiyan Mahmoud Moeinadin Amin NezaratObjective: The current research aims to systematically examine bankruptcy prediction models with the goal of developing a model that serves as a guide for selecting the most suitable tools. These tools should ideally align with the existing data and quality criteria of MoreObjective: The current research aims to systematically examine bankruptcy prediction models with the goal of developing a model that serves as a guide for selecting the most suitable tools. These tools should ideally align with the existing data and quality criteria of bankruptcy prediction models.Research Methodology: To conduct this research, a systematic search was performed on the Web of Science database using keywords such as Bankruptcy, Default, Distress, Failure, Forecasting, Predicting, Prediction, and Insolvency, spanning the years 2015 to 2023. Based on defined inclusion and exclusion criteria, this search yielded 1000 articles, out of which 49 were ultimately selected and analyzed. The findings from these articles were then summarized in tables. Subsequently, major bankruptcy prediction models were compared based on nine key criteria, and final conclusions were drawn.Findings: Artificial neural networks and support vector machines were found to have the highest accuracy, while multiple personality analysis showed the lowest accuracy. Additionally, artificial neural networks, multiple personality analysis, decision trees, and logistic regression require a large training sample to logically identify and precisely classify patterns. However, case-based reasoning, rough sets, and support vector machines can work with smaller sample sizes.Originality/ Value: The outcomes of this research contribute to a comprehensive understanding of the characteristics of tools used in developing bankruptcy prediction models and the shortcomings associated with them. Manuscript profile -
Open Access Article
567 - ارائه یک مدل جدید پیش بینی عمر خستگی کم چرخه آلیاژ منیزیم براساس روش انرژی کرنش پلاستیک تصحیح شده
محمد آزادی غلامحسین فرهیامروزه تکنولوژی به سمت استفاده از موادی همچون آلیاژهای منیزیم، با نسبت استحکام به وزن بالا در قطعات موتوری، تمایل دارد. بطور معمول، از انواع چدن و آلیاژهای آلومینیوم در ساخت سرسیلندر و بلوک سیلندر موتورها استفاده می­شود. اما آلیاژهای منیزیم، خواص فیزیکی و مکانیکی نز Moreامروزه تکنولوژی به سمت استفاده از موادی همچون آلیاژهای منیزیم، با نسبت استحکام به وزن بالا در قطعات موتوری، تمایل دارد. بطور معمول، از انواع چدن و آلیاژهای آلومینیوم در ساخت سرسیلندر و بلوک سیلندر موتورها استفاده می­شود. اما آلیاژهای منیزیم، خواص فیزیکی و مکانیکی نزدیکی به آلیاژهای آلومینیوم داشته و تا حدود 40 درصد وزن را کاهش می­دهند. در این مقاله، یک مدل جدید پیش­بینی عمر خستگی کمچرخه برای آلیاژ منیزیم، بر اساس روش انرژی ارائه شده و به جهت تدوین آن، از نتایج آزمون خستگی کمچرخه روی نمونه­های منیزیمی استفاده شده است. این مدل در مقایسه با دیگر تئوریهای موجود، از پارامترهای مادی کمتری برخوردار است و دارای دقت مناسب­تری می­باشد؛ چراکه در روش انرژی، از رابطه عمر- کار پلاستیک که معادل با ضرب همزمان عددهای تنش و کرنش پلاستیک می­باشد، استفاده می­شود. با توجه به خواص نرم شوندگی آلیاژهای منیزیم و آلومینیوم, انرژی کرنش پلاستیک می­تواند انتخاب مناسبی باشد؛ چراکه در چرخه بارگذاری خستگی، عدد حاصل ضرب تنش در کرنش پلاستیک می­تواند ثابت بماند. همچنین، اثر تنش میانگین بصورت یک ضریب تصحیح در مدل پیش­بینی عمر خستگی کمچرخه اعمال شده است. نتایج حاصل از مدل ارائه شده، تطابق خوبی را با نتایج آزمون نشان می­دهد. Manuscript profile -
Open Access Article
568 - Designing a Model for Predicting the Sales Potential of Iranian Movies (Data-Driven Approach) in Order to Determine the Market Entry Strategy
Babak Hamidia Mohammad Masteri Farahani Mohammad Javad Sohrabi Abbas RahimiHaving a predictive mathematical model regarding the sales potential of movies before the marketing and screening of movies is one of the needs of many producers, Cinema owners, etc. In this research, based on a systematic process and mixed exploratory approach, first t MoreHaving a predictive mathematical model regarding the sales potential of movies before the marketing and screening of movies is one of the needs of many producers, Cinema owners, etc. In this research, based on a systematic process and mixed exploratory approach, first the factors affecting the sales potential of movies were calculated and classified by content analysis method and by selecting the content factors of the film, i.e., the factors affecting the probability of pre-marketing and screening; The status of each of these factors in the top 100 films of a decade of Iranian cinema was examined. The required data were extracted from the statistical yearbook of Iranian film and cinema sales and based on Shannon entropy method and based on real data of 100 popular Iranian films, model coefficients were extracted and finally, a mathematical model to calculate the sales potential of a film up to Extracted before the marketing phase. The results of this study indicate that the 4 main factors of director (with coefficient of 0.25), actor (with coefficient of 0.253), genre (with coefficient of 0.251) and technical quality of film (with coefficient of 0.246) and a sub-factor of film series (with extra score) affect the sales potential of a movie. Manuscript profile -
Open Access Article
569 - A simulation Model to Predict and Improve the Performance of the Working Team and Achieve better Human-Resource Management Strategies (Case Study: Department of Industrial Management, Faculty of Management and Economics, Sciences and Research Branch, Islamic Azad University)
fatemeh eskandar reza radfar abas toloiGiven the importance of the role of human resources in organizations, strategic planning for achieving the optimum number of human resources in an organization is vital. The purpose of this research is to present a model for simulating and predicting team performance in MoreGiven the importance of the role of human resources in organizations, strategic planning for achieving the optimum number of human resources in an organization is vital. The purpose of this research is to present a model for simulating and predicting team performance in industrial management teams in order to identify human-resource performance and improve human-resource management strategies. The factors that influence team performance are identified and extracted from previous studies, and then the timing of each task is examined in three scenarios, i.e. optimistic, probabilistic and Web-based, by identifying the processes that influence team performance. Model inputs are the number of students, the number of faculty, and the number of experts. Based on related studies, team performance outputs are three categories: The number of books, articles and theses; the desirability of team members; and the number of tasks completed, rejected, needed to revise or waiting in queue. The simulation was performed using Any Logic software. The results show that the desirability of the group manager and the training expert have the highest values in most scenarios and the number of tasks in the execution queue has a significant value in all scenarios. In some cases it is essential that new policies be adopted to improve HRM strategies in the industrial management department. Manuscript profile -
Open Access Article
570 - A hybrid bankruptcy prediction model based on GMDH-type neural network and genetic algorithm for Tehran Stock Exchange companies
hosain vazifehdost tayebeh zangenehThis paper proposes a Soft Computing model for effective bankruptcy prediction, based on the integration of Group Method of Data Handling (GMDH) neural network and genetic algorithm which is called here as GA-GMDH. Genetic algorithm (GA) designs the whole architec MoreThis paper proposes a Soft Computing model for effective bankruptcy prediction, based on the integration of Group Method of Data Handling (GMDH) neural network and genetic algorithm which is called here as GA-GMDH. Genetic algorithm (GA) designs the whole architecture of the GMDH network and optimizes its topology. In order to demonstrate the effectiveness of our proposed GA-GMDH model, its performance was compared with performance of the commonly used statistical techniques of logistic regression (LR) and a relatively new artificial intelligent technique of Adaptive Neuro-Fuzzy Inference System (ANFIS). Performance of the designed prediction models depends on the utilized variable selection technique. Therefore, we constructed 12 prediction models through combining the four filtering feature selection methods and the three prediction models. The four feature selection methods of independent samples T-test, correlation matrix (CM), stepwise multiple discriminant analysis (SDA) and principal component analysis (PCA)are combined with prediction models to generate four optimal feature subsets. Empirical data were collected one year prior to failure from Tehran Stock Exchange (TSE) during 1997-2008. For robust assessing of prediction models’ performance, we applied Type-I and Type-II errors, and area under the receiver operative characteristics curve (AUC) measures. Experimental results indicate that our proposed GA-GMDH model has high ability in bankruptcy prediction problem and significantly outperforms ANFIS and LR models in all combinations with four feature selection methods. Meanwhile, the CM method has the best ability in selecting predictive variables in comparison with other feature selection methods. Therefore, CM-GA-GMDH model is determined as the best constructed model for bankruptcy prediction using our particular dataset from TSE. Manuscript profile -
Open Access Article
571 - بررسی جایگاه تیم ملی فوتبال ایران در رده بندی فدراسیون جهانی: مدل پیش بینی ANN و ARIMA
مهوش نوربخش امیر سرشین سردار محمدی -
Open Access Article
572 - پیش بینی موفقیت کشورهای شرکت کننده در بازی های آسیایی بر اساس متغیرهای کلان اقتصادی، سیاسی، اجتماعی و فرهنگی
مهرعلی همتی نژاد محمد رحیم رمضانیان محمد حسن قلیزاده شهرام شفیعی امین قاضی زاهدی -
Open Access Article
573 - Possibility of the Economic Prediction Model based on the Smart Algorithm of the Smart City
mahsa khodadadi Larissa Khodadadi روزبه دبیریSmart cities make better use of space and have less traffic, cleaner air and more efficient city services and improve people's quality of life. The large number of vehicles that are constantly moving through congested areas in smart cities complicates the availability o MoreSmart cities make better use of space and have less traffic, cleaner air and more efficient city services and improve people's quality of life. The large number of vehicles that are constantly moving through congested areas in smart cities complicates the availability of a public parking space. This creates challenges for both traffic and residents. With such a large population, road congestion is a serious challenge. It wastes vital resources like fuel, money and most importantly time. Finding a suitable place to park is one of the reasons for traffic jams on highways. This paper proposes an economic forecasting model based on deep learning for long-term economic growth in smart cities. Traffic management is vital for cities in that it ensures that people can move freely around the city. Many cars trying to reach congested areas in smart cities make it difficult to find a public parking lot. This issue is inconvenient for both drivers and residents. A number of traffic management authorities have implemented an artificial neural network to solve this problem, and modern car systems have come with smart parking solutions. The experimental result of the economic forecasting model based on deep learning improves traffic estimation, accurate prediction of traffic flow, traffic management and intelligent parking compared to existing methods Manuscript profile -
Open Access Article
574 - Explaining and examining the dimensions of distinguishing between philosophical counselling and psychological counselling
Seyed Hesam Hosaini Seyed Salar Hosseini Akbar RahnamaImproving the problems of life in ancient times was a unique role of philosophy. This central role was forgotten due to the dominance of science in the modern era. But in the contemporary era, philosophy has come to its senses and is trying to revive its position in lif MoreImproving the problems of life in ancient times was a unique role of philosophy. This central role was forgotten due to the dominance of science in the modern era. But in the contemporary era, philosophy has come to its senses and is trying to revive its position in life through practical activities such as philosophical counselling. Achieving this goal requires clarifying the boundaries of differentiation between this emerging approach and other forms of psychological counselling. Therefore, this research was done with the aim of explaining the differences between philosophical counselling and psychological counselling. The type of research is applied in terms of purpose and qualitative in terms of approach, and conceptual analysis method and interpretive method were used to explain the purpose. Based on the findings of the research, the differences between these two areas can be explained in terms of the difference in definition, therapeutic role, topic, task and role, skills, goals and the relationship between client and consultant. The results of the research showed that these two areas can support each other as a complement and consider the worldview and mental state of the clients together. Manuscript profile -
Open Access Article
575 - Investigating the effectiveness of group-based life skills management on self-efficacy and academic optimism of 11th grade students in the second year of high school in Ilam city
Massoud Nazarzadeh Tahereh Nakoyan Subhan MomeniSelf-efficacy and academic optimism are one of the important topics during education and they also lead to academic success. On the other hand, teaching life skills in a group way can facilitate academic progress. Management of life skills can lead to academic success a MoreSelf-efficacy and academic optimism are one of the important topics during education and they also lead to academic success. On the other hand, teaching life skills in a group way can facilitate academic progress. Management of life skills can lead to academic success and growth of students.Therefore, the main purpose of the present study was to investigate the effectiveness of group-based life skills training on the self-efficacy and academic optimism of the 11th grade students of the second period of high school for boys in Ilam city. The current study was a semi-experimental one, in which 30 students were selected from the second grade male students using random sampling method. Research tools included self-efficacy and academic optimism questionnaires. Data analysis was done by multivariate covariance analysis using SPSS-22 software. Teaching life skills in a group manner had a favorable and positive effect on increasing academic self-efficacy (0.550) and academic optimism (0.405) in the eleventh grade students of the second period of high school in boys' schools in Ilam city. Based on the findings, it can be concluded that teaching life skills in a group manner increases students' self-efficacy scores and academic optimism, so planners and supervisors of high school education should pay attention to teaching life skills.Based on the findings, it can be concluded that teaching life skills in a group manner increases students' self-efficacy scores and academic optimism, so planners and supervisors of high school education should pay attention to teaching life skills.Based on the findings, it can be concluded that teaching life skills in a group manner increases students' self-efficacy scores and academic optimism, so planners and supervisors of high school education should pay attention to teaching life skills. Manuscript profile -
Open Access Article
576 - The Predictive Validity of Islamic Azad University’s Entrance Examination: Does Access
Mojtaba MohammadiAbstractThe main purpose of the present research was to study the predictive value of theIslamic Azad University’s Entrance Examination (IAUEE) in Iran administered tothose applied for English Language courses. It, furthermore, attempted to investigateprobable cor MoreAbstractThe main purpose of the present research was to study the predictive value of theIslamic Azad University’s Entrance Examination (IAUEE) in Iran administered tothose applied for English Language courses. It, furthermore, attempted to investigateprobable correlation between English Language students’ academic achievementregarding their Grade point Average (GPA) and their entrance admission test resultsand their sex, field of study, or age. To conduct the research, seniorundergraduate students who were admitted to study in all English language fields inIslamic Azad University, Roudehen Branch were randomly selected. Data werecollected regarding their performances in Entrance Examination and their GPAduring the first three years of their study. Data analysis indicated that students’ totalscore in IAUEE had a better predictive value than the English subtest score. Out ofthree English majors under study, admission exam for ELT students had a muchmore recognized predictive value than for students in other courses. Moreover, whileboys’ English proficiency subtest was a better predictor of their academicachievement, girls’ total score proved so Manuscript profile -
Open Access Article
577 - Comparison of forecasting ability of artificial neural network with other forecasting methods: case of sugar beet price
Hamid Mohammadi Farshid Kafilzadeh Mohammad Naghshinehfard Siyamak PishbinThe aim of this study was to forecast nominal and real price of sugar beet and to compare forecasting ability of artificial neural network method with other forecasting methods. The stationary of the series was tested and then, in order to investigate whether series are MoreThe aim of this study was to forecast nominal and real price of sugar beet and to compare forecasting ability of artificial neural network method with other forecasting methods. The stationary of the series was tested and then, in order to investigate whether series are stochastic, nonparametric test of Vald-Wulfowitz and parametric test of Durbin-Watson were applied. Based on the above tests results, nominal price of sugar beet were recognized non-stochastic and predictable, while the real price series was found stochastic. The study period covers 1971-2005. The models used for forecasting were autoregressive, moving average, ARIMA, Single and Double exponential smoothing, harmonic, ARCH and artificial neural network. Based on the lowest forecasting error criterion, harmonic model forecasted nominal price of sugar beet with lowest forecasting error. The amount of nominal series forecasted by different models was at range of 344000-396000 and 398000-448504 rials per ton for 2004 and 2005, respectively. The happened values of nominal price series for 2004 and 2005 were 387200 and 447000 rials per ton, respectively. Manuscript profile -
Open Access Article
578 - Examining Economic Hardship and Cosmopolitanism on Animosity and Consumer Purchase Intention (Case Study: Products of Pars Khazar Company)
Esmaeil Akbari Shabkhoslati Elham Faridchehr Majid AhmadiThe purpose of this study was to investigate the effect of economic hardship and cosmopolitanism on animosity and consumer purchase intention at Pars Khazar Company in Tehran. The purpose of this study is applied and based on data collection method, descriptive correlat MoreThe purpose of this study was to investigate the effect of economic hardship and cosmopolitanism on animosity and consumer purchase intention at Pars Khazar Company in Tehran. The purpose of this study is applied and based on data collection method, descriptive correlational type. The statistical population of the research is all the customers of Pars Khazar Company, based on Cochran's formula, 384 people were selected as a sample and 384 questionnaires were distributed by simple random method. Th e reliability of the questionnaire was measured using Cronbach's alpha coefficient, which was 0.803. The validity of the research instrument was also evaluated by confirmatory factor analysis technique. Then the data were analyzed by structural equation modeling using Smart-PLS software. The results of the research hypotheses show that economic hardship and cosmopolitanism on animosity, animosity o n quality judgements an d consumer purchase intention, and quality judgements affects the consumer purchase intention. Manuscript profile
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