List of Articles Multivariate regression

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  1 - Twentieth Century Urbanization in Bangladesh and a Spell of High and Unsustainable Urban Growth
  Md. Abdur Rouf
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  2 - Effective factors on abnormal return of IPO in Tehran stock exchange
  منصور گرکز حمیدرضا وکیلی فرد اکتای یمرعلی
  In this research, the effective factors on abnormal return of IPO companies inTehran Stock Exchange from 1990 until 2007 have been studied. So, for this westudied 73 qualified companies according to elimination method and studied them forperiods pf 12 and 24 months afte More

  In this research, the effective factors on abnormal return of IPO companies inTehran Stock Exchange from 1990 until 2007 have been studied. So, for this westudied 73 qualified companies according to elimination method and studied them forperiods pf 12 and 24 months after entrance to stock exchange. Amazing six variablesof firm size, ownership type forecast error of earnings per share return on equity netprofit margin ratio and debt to net assets ratio , just return on equity (adversely) anddebt to net assets ratio (directly) had a meaning full relationship with abnormal return.But, in general, the analysis of multivariate regression showed that every sixindependent variable have the ability of justifying the 13.7 percent of abnormal returnat the time. Manuscript profile
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  3 - Evaluation of classic semi-permanent sprinkler system and modeling evaporation losses and wind drift in ADF 25‌˚ nozzle sprinkler model in Moghan region
  majid raoof یاسر حسینی fardin Nazari-Gigloo
  Optimized management and utilization of any system requires knowing the working conditions of the system, and optimized utilization becomes possible by evaluating the way the system works. Since various regions in Iran have arid and semi-arid climates, obtaining the act More

  Optimized management and utilization of any system requires knowing the working conditions of the system, and optimized utilization becomes possible by evaluating the way the system works. Since various regions in Iran have arid and semi-arid climates, obtaining the actual wind drift and evaporation losses and also making optimized use of water has a great importannce. The present research intended to evaluate a classic semi-permanent sprinkler, to measure wind drift and evaporation losses, and to introduce an optimized model by using multivariate regression for the study region. The study was conducted in Part of the Moghan agro-industrial complex in Ardabil province at wind speeds of 0-3 and 3-6 and higher than 6 meters per second with three replications. Results in ADF 25º nozzle sprinkler model indicated that the efficiencies of the system at wind speeds of 0-3, 3-6, and higher than 6 meters per second were 82, 66, and 43 percent, respectively, and wind speed, temperature, relative humidity, nozzle diameter, and vapor pressure deficit (saturation deficit) were among the factors that influenced wind drift and evaporation losses. The wind factor had the most and vapor pressure deficit the least effect on wind drift and evaporation losses. Furthermore, the equation of the best fit line to the measured values for wind drift and evaporation losses under the prevailing atmospheric conditions in the region was as follows and the difference between results of the model and observed data was not significant in 1% level of confidence. Moreover, the measured and the modeled percentages obtained for wind drift and evaporation losses varied from 6 to 34 and from 11to 35 percent, respectively. Manuscript profile
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  4 - Prediction of remained pyrite fraction within a coal waste pile with using of multivariate regression method
  Behshad Jodeiri Shokri Faramarz Doulati Ardejani Sadegh Karimpouli
  Background and Objective: Acid mine drainage (AMD) is one of the most environmental problems which is caused by mining activities. It may be generated from oxidation of sulfide minerals (specifically pyrite) in mining wastes, ore and mineral processing. As a result, pre More

  Background and Objective: Acid mine drainage (AMD) is one of the most environmental problems which is caused by mining activities. It may be generated from oxidation of sulfide minerals (specifically pyrite) in mining wastes, ore and mineral processing. As a result, prediction and measurement of pyrite can play a key role in investigation of AMD process. In this paper, a relationship based on multivariate regression is suggested for predicting of remained pyrite fraction within a coal waste pile located nearby Alborz- Sharghi coal washing plant. Method: For this purpose, the model uses the most important factors (independent variables) including depth, mole fraction of oxygen, local temperature and cumulative annual precipitation (from the initial deposition of the wastes within the pile) as input parameters and returns the remaining pyrite fraction (dependent variable) in the related depth of the pile as its output. Findings: The results of the laboratory experiments reveal that the fraction of pyrite remaining gradually increased at the lower depth where the oxygen diffuses from the surface to 2 m of the pile. A comprehensive statistical analysis was conducted after obtaining and collecting of the required data which caused all the possible relationships among the target and independent variables to be suggested and presented. Then, the best model (relationship) according to Efroymson’s the step wise regression method was presented to predict of the remained pyrite fraction within the pile. Discussion and discussions: The relatively high confidence level of the suggested model (87%) reveals its appropriate reliability. A strong correlation (R2=90%) between validation data and suggested model also confirms the desirable reliability of the model. The proposed model is recommended to be applied in similar coal waste piles and will economize time and cost in investigation of AMD process on the environmental management issue of mining wastes.   Manuscript profile
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  5 - Impact of macroeconomic variables on unobserved systematic risk using Kalman filter
  Majid Hatef Vahid Abbas Saleh Ardestani
  The main purpose of this study was to investigate the effect of macroeconomic variables on unobserved systematic risk using the Kalman filter. Systematic risk indicates the degree of dependence between changes in share prices and changes in the market index. However, th More

  The main purpose of this study was to investigate the effect of macroeconomic variables on unobserved systematic risk using the Kalman filter. Systematic risk indicates the degree of dependence between changes in share prices and changes in the market index. However, the amount of systematic risk can be very different from the expected amount, due to the confusion in stock price changes, resulting from emotional transactions, overreactions and price manipulation. Therefore, it is necessary to control the effects of these disturbances in measuring systematic risk. The method of the present study is descriptive-correlational which was performed using statistical methods to examine the relationships between variables based on Ives software. To analyze the data in this study, it is suggested to use Kalman filter. Also, filtered and turbulent values have been used under the heading of unobserved systematic risk. According to the obtained result, it can be said that all variables have a significant relationship with the systematic risk not observed in the model. Then, using data analysis, the hypotheses were examined. The results obtained in relation to statistics and a significant level show the confirmation of all hypotheses in terms of the impact of economic variables on the components of inflation, economic growth, exchange rate, stock market index and volume. Money showed unprecedented systematic risk. Also, the effect of different variables and finally the estimation of coefficients showed that the highest coefficient among the variables is related to inflation index and stock market. Manuscript profile
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  6 - Evaluation of soil salinity by analyzing Landsat-8 images and field Observations (Case study: Behesht-e- Gomshodeh, Fars province)
  Mohamad Kazemi Fariborz Mohammadi Ali Reza Nafarzadegan
  Soil salinity is considered as one of the potential environmental hazards. The purpose of this study was to find the best index and the most suitable relationship for estimating soil salinity and its mapping using remote sensing data. At the first step, random sampling More

  Soil salinity is considered as one of the potential environmental hazards. The purpose of this study was to find the best index and the most suitable relationship for estimating soil salinity and its mapping using remote sensing data. At the first step, random sampling was performed using fishnet method and surface soil electrical conductivity (EC) measurements. Then, the threshold levels (92%, 95%, and 98%) were applied to the output images of each indicator. The methodology included using the least squares fitting (LS-fit) technique and principal components analysis (PCA) for halite and gypsum minerals, determining the correlation between the output of indices and ground data, and performing clustering and factor analysis between EC and output images. In order to select the best model derived from Landsat-8 band combinations and the amount of salinity, collinearity test, Durbin-Watson test, and backward multivariate regression were employed. The Cohen‘s kappa coefficient was also applied to evaluate the multivariate regression formed by Landsat-8 bands. The performance of the indicators was evaluated based on four criteria of root mean square error (RMSE), mean bias error (MBE), mean absolute error (MAE) and R-squared (R2). The results of the factor analysis showed the smallest distance between the EC, salinity index (SI) and brightness index (BI). The SI with an amount of 0.89 had the highest Pearson correlation with EC. In the dendrogram diagram, SI index with EC was placed in a cluster, and the RMSE, MBE, MAE and R2 values of the SI index were estimated to be 0.16, 0.11, 0.12, and 0.76, respectively. Compared to the rest of the indicators and linear, multivariate regression (with Cohen‘s kappa coefficient of 60%,), the SI index has provided better outcomes. Manuscript profile
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  7 - Comparability of Financial Reports and Negative Skewness of firm-Specific Monthly Returns: Evidence from Iranian firms
  Mehdi Safari Gerayli
  10.22034/amfa.2019.1864043.1196
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  8 - بررسی توابع انتقالی رگرسیون چند متغیره، شبکه پرسپرترون چند لایه و توابع پایه شعاعی جهت برآورد ظرفیت تبادل کاتیونی خاک‌های شمال اهواز
  علی صالحی کامران محسنی فر علی غلامی
  برای تخمین ظرفیت تبادل کاتیونی خاک (CEC) به روش غیر مستقیم از توابع انتقالی استفاده می‌شود. چون (CEC) یکی از شاخص‌های مهم حاصلخیزی خاک است که به دلیل هزینه‌بر و وقت‌گیر بودن کمتر به صورت مستقیم اندازه‌گیری می‌شود. هدف از این تحقیق برآورد (CEC) خاک با استفاده از رگرسیون More

  برای تخمین ظرفیت تبادل کاتیونی خاک (CEC) به روش غیر مستقیم از توابع انتقالی استفاده می‌شود. چون (CEC) یکی از شاخص‌های مهم حاصلخیزی خاک است که به دلیل هزینه‌بر و وقت‌گیر بودن کمتر به صورت مستقیم اندازه‌گیری می‌شود. هدف از این تحقیق برآورد (CEC) خاک با استفاده از رگرسیون چند متغیره و شبکه‌های عصبی مصنوعی از روی خصوصیات زودیافت خاک می‌باشد. به این منظور اندازه‌گیری‌ها برای 100 نمونه خاک شامل 1000 اندازه‌گیری شامل اندازه توزیع ذرات خاک، جرم مخصوص ظاهری، مواد آلی، آهک، تخلخل، میانگین هندسی قطر و انحراف معیار هندسی، انجام شد. پس از شناسایی داده‌های پرت و حذف آنها آزمون نرمال بودن داده‌ها صورت گرفت. با استفاده از نرم‌افزار SPSS رگرسیون چند متغیره بین (CEC) و ویژگی‌های زودیافت خاک برقرار شد. سپس بسط توابع انتقالی برای ظرفیت تبادل کاتیونی خاک با استفاده از پارامترهای موجود با شبکه عصبی پرسپترون چند لایه (MLP) و شبکه عصبی تابع پایه شعاعی (RBF) انجام شد. نتایج نشان داد مواد آلی و رس خاک که منابع اصلی بار منفی خاک مـیباشـند با بالاترین ضریب تبیین 0.97 در برآورد CEC نقش دارند و مدل رگرسیون چند متغیره به طور کلی با ضریب تبیین 0.87 روش نسبتا مناسبی جهت برآورد CEC می‌باشد و شبکه MLP،  با تابع انتقال تانژانت سیگموئید در لایه میانی و تابع انتقال خطی در لایه خروجی و الگوریتم آموزشی بیزین با ضریب تبیین 97/0 و میانگین مربعات خطای013/0 قادر است CEC را با خطای کمتری برآورد کند. برای شبکه RBF ضریب تبیین برابر 55/0 و خطای 017/0 در مرحله تست شبکه بدست آمد. درمجموع با توجه به نتایج حاصل مشخص شد که MLP به دلیل اینکه برای دادههایی که به صورت خطی قابل تفکیک نیستند را میتواند بهتر متمایز کند، دارای خطای کمتر و بعد از آن رگرسیون چند متغیره بهترین مدل‌ها در مدل‌سازی و تخمینCEC می باشد درصورتی که شبکه های RBF  به دلیل حساس بودن به ورودیها از دقت کمی در منطقه مورد مطالعه برخوردار می‌باشند. Manuscript profile
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  9 - آنالیز منطقه ای جریان‌های کمینه در حوزه‌های آبخیز کرخه و کارون
  هدایت الله زرین فرود شریفی مهدی وفاخواه
  در طراحی و اجرای پروژه‌های آبی کوچک در کشور، عمدتا به برآورد سیل توجه شده است و به مساله خشک سالی در برنامه ریزی منابع آب، کمتر اهمیت داده شده است. در این تحقیق به منظور برآورد جریان کمینه، از آمار موجود 28 ایستگاه هیدرومتری در حوزه‌های کرخه و کارون که دارای شرایط مناسب More

  در طراحی و اجرای پروژه‌های آبی کوچک در کشور، عمدتا به برآورد سیل توجه شده است و به مساله خشک سالی در برنامه ریزی منابع آب، کمتر اهمیت داده شده است. در این تحقیق به منظور برآورد جریان کمینه، از آمار موجود 28 ایستگاه هیدرومتری در حوزه‌های کرخه و کارون که دارای شرایط مناسب از نظر طول دوره آماری بودند، استفاده شد. سپس منحنی تداوم جریان برای هر کدام از ایستگاه‌ها ترسیم گردید ومقادیر دبی جریان‌های کمینه مورد نیاز آنها استخراج گردید. به منظور تعیین مهمترین عوامل مؤثر بر جریان کمینه، 21 پارامتر مؤثر بر جریان کمینه مانند پارامترهای فیزیوگرافی، اقلیمی و زمین شناسی به وسیله سیستم اطلاعات جغرافیایی برآورد گردید. با استفاده از روش تجزیه و تحلیل عاملی، عواملی که کمترین هم بستگی را با هم نشان دادند، انتخاب شدند. این عوامل به ترتیب اهمیت، شامل شیب متوسط حوزه، مساحت، ارتفاع متوسط حوزه، ضریب گراولیوس و شیب آبراهه اصلی بوند، که 1/80 درصد از تغییرات در داده‌های اصلی را توضیح می دهند. در ادامه، تحلیل منطقه ای به روش رگرسیون چند گانه برای به دست آوردن روابطی بین جریان کمینه و ویژگی‌های حوزه آبخیز صورت گرفت. در نهایت به منظور مقایسه و ارزیابی صحت مدل‌های برآوردی، اطلاعات 9 ایستگاه شاهد مورد استفاده قرار گرفت و مقادیر دبی جریان کمینه بر اساس مدل‌های به دست آمده  و با مقادیر متکی بر ایستگاه‌های شاهد، مقایسه گردید و در نهایت، نتایج نشان دادند که مدل‌های به دست آمده در این منطقه، در سطح معنی داری 99 درصد، قابل قبول می باشند. در نهایت بررسی جریان‌های کمینه و تهیه مدل‌های منطقه ای جریان‌های کمینه، در مقیاس سراسری، برای برنامه ریزی مدیریت آبی کشور و استفاده از سایر خصوصیات مؤثر بر روی جریان‌های کمینه، مانند درصد پوشش گیاهی یا شاخص‌های مربوط به خاک شناسی و کاربری اراضی و در نهایت بررسی اثرات تغییر اقلیم بر جریان‌های کمینه، پیشنهاد می گردد. Manuscript profile
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  10 - Multivariate Analysis of Variance (MANOVA) and Multivariate Regression in Determining Thermal Conductivity of Nanofluid for Use in Mechanical Systems
  Mohammad Reza Ghalani Moslem Barzegari Ashkan Ghafouri
  Statistical methods are used in the analysis of all types of data. In this paper, using multivariate analysis of variance and multivariate regression, the data related to the thermal conductivity of nanofluids have been analyzed and the results of the two methods have b More

  Statistical methods are used in the analysis of all types of data. In this paper, using multivariate analysis of variance and multivariate regression, the data related to the thermal conductivity of nanofluids have been analyzed and the results of the two methods have been compared. A two-step method was used to prepare ethylene glycol-magnesium oxide nanofluid. In order to prepare the nanofluid by suspending the nanoparticles in the base fluid, an ultrasonic homogenizer was used. For this purpose, nanoparticles with diameters of 20, 50, and 100 nm in volume fractions of 0.25, 0.5, 0.75, 1, and 1.25% have been used at temperatures of 25, 30, 35, 40, 45, and 50 degrees Celsius. Transient hot wire method was used to measure thermal conductivity in different volume fractions. Then the obtained experimental values were analyzed using SPSS.26 software. The coefficient of determination and the graphs of the errors obtained in the two methods showed that when the independent variables are defined as grouped, the use of multivariate analysis of variance can better describe the dispersion of the thermal conductivity. Manuscript profile
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  11 - Comparing the Performance of Neural Networks and Multivariate Regression in the Estimation of Housing Prices (Case Study: Ahvaz City)
  said amanpour ismail soleimanirad leila keshtkar Sadegh Mokhtari
  Housing is a basic need in the community always. Housing market has been one of the most fluctuation sectors of the economy of Iran country over the past years. Since the housing sector changes have a great impact on other sectors of the economy, so one of the significa More

  Housing is a basic need in the community always. Housing market has been one of the most fluctuation sectors of the economy of Iran country over the past years. Since the housing sector changes have a great impact on other sectors of the economy, so one of the significant needs of housing is predicting the price of this good. In this context, in this study by using of multi-layer perceptron neural network, presented a model to predict housing price in the city of Ahvaz and the results compared with the multivariate regression model. This study is a practical–developmental and its method is analytical- descriptive. To do this, 233 samples of statistical unit in 1392 were analyzed on the basis of 16 relevant variables. The results show that multi-layer neural network with 91 percent accuracy have been more accurate compared with the multivariate regression in the predicting housing prices. In addition to evaluating the performance of models coefficients R^2 and RMSE were used. Coefficient of determination (R^2) by using multivariate regression is .789 and its value for neural network is .918. The result of the regression model indicates weaker performance of this model compared to artificial neural network approach. Manuscript profile
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  12 - Spatial analysis and modeling the relationship between atmospheric action centers with widespread anomalies precipitation of Iran
  Hosain Mohammadi Faramarz Khoshaghlagh ghasem azizi Mohammad Amin Heidari
  Variability is one of inherent properties of the climate system. In addition to the dynamic nature, the climate system is extremely intertwined nature also, so that its components interact with each other and eventually they change each other.. In general, the climate o More

  Variability is one of inherent properties of the climate system. In addition to the dynamic nature, the climate system is extremely intertwined nature also, so that its components interact with each other and eventually they change each other.. In general, the climate of a region or geographic location is controlled by various factors, including Atmospheric Action Centers (AAC's). AAC's behaviors have an effective role in short and long term changes in weather and climate conditions and also their components. AAC's can change the climate system. A climatic index is defined here as a critical value that can be used to describe the states and the changes in the climate system. Changes on climate are much slower than on the weather, that can change strongly day by day. Each climatic index is based on certain parameters and describes only certain aspects of the climate, so there are a variety of climate indices that have been defined and examined in numerous publications. For each climate index there is a defining equation that uses the so-called climate elements. These are measurable parameters that influence the properties of the climate system, primarily, for example, atmospheric parameters such as air pressure, air temperature, precipitation and solar radiation, but also non-atmospheric parameters such as sea surface temperature or ice cover. Manuscript profile
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  13 - Evaluation of the impact of urban-rural migrations on land use changes in metropolitan cities (A Case study of Tabriz Metropolis)
  gholamreza mokhtari farivar karim hoseinzade delir hosein nazamfar
  With their many functions, metropolitan cities have strong relationships with the peripheral areas and especially the villages of the penetration zone, and this has a profound impact on the economic, social, cultural, and even physical aspects of the villages. Economic More

  With their many functions, metropolitan cities have strong relationships with the peripheral areas and especially the villages of the penetration zone, and this has a profound impact on the economic, social, cultural, and even physical aspects of the villages. Economic growth of cities is due to their economic relations. The city and the countryside have the advantages of attracting rural employment, creating out-of-village job opportunities and rural-urban migration. The metropolis of Tabriz, in various historical periods, has played a strong transnational role from Eastern Europe to South and Central Asia, which shows its undeniable role in taking on some strong professional functions to perform this task. This interconnection between the metropolitan city of Tabriz and its sphere of influence, on one hand, extends the physical development of the city to its national metropolis, and on the other hand, the physical development of the surrounding villages and extensive user changes in these villages, along with widespread demographic, economic and cultural changes will be obtained. This issue is the main subject of the present research and its main objective is to monitor and evaluate the role of the expansion of the metropolitan city of Tabriz by urban-rural migrations and its impact on physical changes, in particular, land use changes in the urban areas. This study concerning its purpose is a descriptive one and as the methodology is considered is an applied research which has been developed based on the questionnaires used in the study and analyzing its items. To achieve the objectives of the study, we used the Cronbach, Kolmogorov-Smirnov, T-Student and multivariate regression tests. The results show strong correlation between migration and change indicators if more than 85% of land use variations are expected by the migratory variables. Manuscript profile
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  14 - Effectiveness of Crop Advisory Services in Aurangabad District of Maharashtra in India
  Bhaskar Pant Alpa Rathi Anshul Rathi
  The project was undertaken to study the evaluation of effectiveness of crop advisory services and suggested measures for filling the gap in Aurangabad district of Maharashtra in India. The survey was carried out in 2010. The data was collected with the help of a specifi More

  The project was undertaken to study the evaluation of effectiveness of crop advisory services and suggested measures for filling the gap in Aurangabad district of Maharashtra in India. The survey was carried out in 2010. The data was collected with the help of a specifically designed and pre-tested questionnaire. The project carried out in catchment area of advisory services has given substantial insight on the current status of different dimensions of advisory services running in Aurangabad and also recommends strategies to make advisory services accessible to all. The farmer’s willingness to pay assumes a key role in determining the success of a cost-recovery strategy. During the study it was interesting to note that of all the 115 respondents 46.67% agreed that their critical need was supply of inputs followed by credit purchase on which the advisory services provider should focus. The dissemination channels were not utilized properly. The results of correlation study indicate that the recommendations by the advisory services and the results after advise have a positive correlation with increase in yield showing the effectiveness of these crop advisory services. The results of multivariate regression indicated that the cropping and harvesting method, credit access, input supply linkage, insurance, age, education and interaction with other farmers have the main role in showing the variations of attitude to adoption of the advisory services. Manuscript profile
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  15 - Prediction of Soil Organic Carbon (SOC) in Semi-Arid Rangeland Using Multivariate Statistical Analysis based on Remotely Sensing Data (Case study: Neyshabur Rangeland, Khorasan-Razavi Province, Iran)
  Hamid Reza Matinfar Ahmad Reza Pilevari Akbar Sohrabi
  10.30495/rs.2023.689407
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