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Open Access Article
1 - Designing and explaining the ranking model and credit rating transfer using data envelopment analysis model and Markov chain
farid heidarifard farhad hanifi gholamreza zomorodianIn ‏this ‏study, ‏using ‏factor ‏analysis ‏technique ‏and ‏Delphi ‏method, ‏the ‏variables ‏affecting ‏credit ‏risk ‏were ‏selected ‏and ‏entered ‏into ‏the ‏data ‏envelopment ‏a MoreIn ‏this ‏study, ‏using ‏factor ‏analysis ‏technique ‏and ‏Delphi ‏method, ‏the ‏variables ‏affecting ‏credit ‏risk ‏were ‏selected ‏and ‏entered ‏into ‏the ‏data ‏envelopment ‏analysis ‏model, ‏and ‏the ‏efficiency ‏scores ‏of ‏Tejarat ‏Bank ‏legal ‏and ‏credit ‏companies ‏listed ‏on ‏the ‏stock ‏exchange ‏were ‏obtained ‏using ‏them. ‏Then ‏the ‏ranking ‏is ‏done ‏by ‏the ‏model ‏of ‏Fitch ‏Institute ‏and ‏using ‏the ‏results, ‏the ‏transfer ‏of ‏customers ‏in ‏different ‏groups ‏is ‏predicted ‏using ‏the ‏Markov ‏chain ‏process. ‏The ‏results ‏of ‏data ‏envelopment ‏analysis ‏indicate ‏that ‏7 ‏companies ‏were ‏identified ‏as ‏efficient ‏in ‏the ‏financial ‏approach ‏and ‏12 ‏companies ‏in ‏the ‏combined ‏approach. ‏The ‏results ‏of ‏the ‏Markov ‏chain ‏show ‏that ‏the ‏average ‏probability ‏of ‏stopping ‏at ‏the ‏current ‏rank ‏in ‏1400 ‏in ‏the ‏financial ‏condition ‏is ‏46% ‏and ‏in ‏the ‏combined ‏mode ‏is ‏53% ‏and ‏the ‏average ‏probability ‏of ‏improvement ‏of ‏the ‏companies ‏is ‏23% ‏and ‏the ‏average ‏probability ‏of ‏the ‏decline ‏is ‏20%. ‏Turns.. Manuscript profile -
Open Access Article
2 - Research on Tehran’s dry and wet periods using second grade Markov chain Model
پرویز Kerdavani حسین Mohamadi مژگان AfsharIn order to Statistically and Synoptically analyze and predict the dry and wet periods inTehran during the cold period, the days with 0/1 milimeter rain or more , mehrabadstation was daily chosen and surveyed as wet days during 1985-2003. The secondgrade markov chain mo MoreIn order to Statistically and Synoptically analyze and predict the dry and wet periods inTehran during the cold period, the days with 0/1 milimeter rain or more , mehrabadstation was daily chosen and surveyed as wet days during 1985-2003. The secondgrade markov chain model was used For determinig dry and wet periods. At firstfrequancy wet and dry days according to their continuation were classified andfrequancy eash one was studied individually.Tthen the possibility of every sequencewas calculated monthly and a six month of cold ness period.The most frequancy of rainy days 51 days and its least is 25 days a year. Marchwith 188 and October with 81 days rain is the Maximum and the Minimum frequency.1995 and 1996 years have been the driest and wettest years.After determining thesequences , the survey of effective pressure patterns in creating rain during the days 27to 30 of November ,1 to 7 of December 2003 as a longhest period and 10 to 13 ofDecember 1995 as a period of 4 days of wetness during the driest year , the surveyperiod was synoptically analyzed for this reason. It has been necessary to use sea levelpressure maps and 500 hp and also maps of direction and speed of the wind andspessific humidity 700 hp.The comparison of the frequency of predicted sequences with the frequancy ofobserved sequences , shows markov chain model exactness in predicting the dry andwet sequences of Tehran region which have sharp mismathch of rain.In synoptically maps it was specified that the most important source of humidityin Iran have been the Red sea, Arab sea, Adan gulf, which concidence of these wetnesssources with the Persian gulf and Saudi Arabia high pressure has caused moretransition of wetness into Iran and Tehran. Manuscript profile -
Open Access Article
3 - 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
4 - Land use changes by using RS and Markov chain technique in the south-west of Tehran
Faezeh RajabzadehLand use changes investigation requires the use of rapid methods and new techniques, respectively. The use of remote sensing and GIS and integrating them with accurate information and field data prepared multipurpose decision. In this study, used images of Landsat 2, se MoreLand use changes investigation requires the use of rapid methods and new techniques, respectively. The use of remote sensing and GIS and integrating them with accurate information and field data prepared multipurpose decision. In this study, used images of Landsat 2, sensor MSS June 1975, Landsat 7, ETM + 2002, and Landsat 8 sensor OLI June 2013, from USGS site for developing maps and survey land use changes over the period of 38 years in ENVI and ERDAS software. The Landsat 5, TM sensor image, June 1991, used to prepare land use maps and compared with 2002 and 2013, to predict land use change in 2024. Results related to land use changes in the past 38 years show a reduction of 12% (9/7060 hectare) orchard area and an increase of 7% and 5% of residential areas and agricultural lands, respectively. Also the predicted land use changes in 2024 represents a decrease of 2% compared to the current state of the orchard, while the almost constant level of agricultural land, and residential area will increase 2 percent. Manuscript profile -
Open Access Article
5 - Assessment of climate change uncertainty and its effects on the probability of the Jamishan dam inflow frequency
مریم حافظ پرست مودت علی بافکار الهه پناهیIn order to assess the uncertainty of climate change and its effect on the discharge into the Jamishan dam located in the northwestern province of Kermanshah changes in temperature and precipitation parameters in the periods 2020-2039 and 2040-2059 were calculated using MoreIn order to assess the uncertainty of climate change and its effect on the discharge into the Jamishan dam located in the northwestern province of Kermanshah changes in temperature and precipitation parameters in the periods 2020-2039 and 2040-2059 were calculated using a combination of weighted average seven climate model output under three emission scenarios A1B, B1 and A2 respectively, The daily rainfall and temperature forecasts for future periods under each climate scenario was entered to rainfall-runoff calibrated and validated model ‘IHACRES’ and the daily runoff of future periods under each scenario was predicted. In order to determine periods of high-water and water shortage in the status quo and future periods, using Markov chain transition probability matrix, the Frequency months of wet, normal and drought were calculated. The results showed that in the period 2020-2039, annual rainfall decreases and temperature increases. In the period 2040-2059 the annual temperature changes are most severe between -0.66 and +2 °C. A1B and B1 scenarios show annual rainfall and runoff reduction and increase in the A2 scenario. Manuscript profile -
Open Access Article
6 - Land use management change in Marvdasht plain - Fars Province
Khatereh Nobaharan Shahla Mahmodi seyad ali abtahiIn Iran, there are many investigations about landuse change which usually mention negative side. In this research landuse/land cover change trend investigate with use of landsat image and Markov chain in IDRISI Andes V15 software at the period of 1990, 2004 and 2018, an MoreIn Iran, there are many investigations about landuse change which usually mention negative side. In this research landuse/land cover change trend investigate with use of landsat image and Markov chain in IDRISI Andes V15 software at the period of 1990, 2004 and 2018, and predicted changes for 2032 in Marvdasht region. There are about 196000 ha, equal to 91%, that used for cultivation, while range land, bare land and urban area are about 20000 ha, respectively 4.9, 2.7 and 1.6 percent of region area. In 28 years, from 1990 to 2018, agricultural and range lands decrease about 9%, while bare lands and urban area increased. At this period bare lands increased from 2.7% to 11.29% of the total region area. In general, the results of this study indicate that in the long-term, agricultural lands are declining and bare land is increasing, Hence immediate management plans are necessary to prevent the destruction of agricultural land. Manuscript profile -
Open Access Article
7 - Effect of Land Use Trends on the Amount of Agricultural Water Consumption in Urmia Lake Watershed in the Next 20 Years Using Markov Chain
Kiyoumars Roushangar Mohammad Taghi Aalami Hassan GolmohammadiBackground and Aim: Reducing the water level of Urmia Lake and its effects on the environment around the lake has been one of the important national and international issues and challenges in the last two decades. In accord with the studies, one of the critical factors MoreBackground and Aim: Reducing the water level of Urmia Lake and its effects on the environment around the lake has been one of the important national and international issues and challenges in the last two decades. In accord with the studies, one of the critical factors affecting this declining trend has been the rise in harvest, especially for agriculture. Accordingly, the purpose of this study is to simulate the future status of water resources in the Urmia Lake basin, influenced by the area of agricultural land uses.Method: For this purpose, Landsat satellite image data for the period 2000 to 2020 are firstly classified using the SVM algorithm in ENVI5.3 software and the classification accuracy is analyzed using the Kappa Coefficient algorithm.In the following, the statistics and information related to the change of cultivation pattern (from arable to garden) and water sources discharging Lake Urmia are calculated. In the next step, the simulation of land use changes for 2030 and 2040 is done using two LCM and CA-MARKOV methods. And finally, after determining the amount of changes in each land use, the amount of water required for agricultural affairs in the catchment is simulated using NETWAT model.Conclusion: The results show that the area of two uses, irrigated agriculture and garden will increase from 1450 and 395 square kilometers in 2000 to more than 3600 and 1650 square kilometers in 2040, respectively, This will increase the amount of water Needed or agriculture from 1,500 million cubic meters in 2000 to more than 4,100 million cubic meters in 2040.Results: From 2000 to 2020, water consumption in irrigated agriculture has increased by 1253.05 Km2; which according to Markov's prediction method, this amount will reach 2049.54 Km2 in 2040 that raises the amount of water consumption by 1 billion and 473 million cubic meters. The gardens land use has increased by 688.02 Km2 from 2000 to 2020, and according to Markov's prediction method, this amount will reach 1276.14 Km2 in 2040, which raises the amount of water consumption by 703 million cubic meters. From 2000 to 2020, 367.06 Km2 has been added to the drayland farming, which according to the prediction of Markov method, this amount will reach 531 Km2 in 2040, which soars the amount of water consumption by 253 MCM. Manuscript profile -
Open Access Article
8 - Investigating the transmission potential of land use and land cover using Similarity Weighted Instance based Learning, Logistic regression and Geomod methods (Case study: Bastam basin, Selseleh city)
soheila naseri rad Hamed Naghavi Javad Soosani seyed ahmadreza nouredini sasan vafaeiBackground and Objective: Assessing and estimating the high-accuracy transmission potential is an important step in the process of land use and land cover changes modeling and predicting. The aim of this study is to investigate the transmission potential of land use and MoreBackground and Objective: Assessing and estimating the high-accuracy transmission potential is an important step in the process of land use and land cover changes modeling and predicting. The aim of this study is to investigate the transmission potential of land use and land cover changes using Similarity Weighted Instance based Learning, Logistic regression and Geomod methods. Method: The land use and land cover maps for a 30-year period (1985-2015) were prepared using Landsat 5 and 8 satellite imagery. Land use and land cover transmission potential modeling was done using Similarity Weighted Instance based Learning, Logistic regression and Geomod methods and effective variables in the process of change. The accuracy of the results obtained from the models was determined by comparing with ground reality map for mentioned year. Findings: The Kappa coefficient of Similarity Weighted Instance based Learning, Logistic regression and Geomod were 0.84, 0.76 and 0.67, respectively. The investigating predicted maps for 2030 prepared by Similarity Weighted Instance based Learning and Markov chain showed that the area of residential areas, gardens and agricultural lands is increasing and the area of bare land, forests, pastures and water resources will have a decrease trend. Discussion and Conclusion: Finally, the results indicate a relatively high accuracy of three methods in estimating the transmission potential for land use and land cover changes, but according to the kappa coefficients, the accuracy of Similarity Weighted Instance based Learning method more than the other two methods. Manuscript profile -
Open Access Article
9 - Study of Persistence of Polluted Days with Carbon Monoxide (CO) in Tehran City Using Markov Chain Model
Jaber Rahimi Ali Rahimi Javad BazrafshanAbstractIntroduction & Objective: Air pollution is one indication of the urbanization, populationincensement, excessive use of fossil fuel resources, lack of utilizing environmentally friendlytechnologies and most importantly lack of proper environmental management MoreAbstractIntroduction & Objective: Air pollution is one indication of the urbanization, populationincensement, excessive use of fossil fuel resources, lack of utilizing environmentally friendlytechnologies and most importantly lack of proper environmental management are some the factorswhich play big roles in this matter. Establishment more than ten million people and excessiveconcentration of industries and factories, alongside with the geographical situation, topography andspecific climatic region, have made Tehran one of the seven polluted cities in the world. In theassessment of air quality, concentration of carbon monoxide gas (CO), among the various pollutants,has a main role and importance.Materials & Methods: In this study, the probability of persistence of two to seven days unauthorizedamounts of pollutants CO in city of Tehran was investigated. For this purpose, the 5-year data (2002-2006) related to five stations measuring air quality of pollution control companies of Tehran werecollected and then using first-order, two-state Markov chain were modeled.Results & Discussion: Results showed that the highest probability of persistence of pollutant CO existin Fatemi station, Bazar and Aqdasiyeh stations are sat at next orders. Many months of the year,Fatemi station has the highest probability of CO and two stations, Bazar and Aqdasiyeh, are located innext ranks. Meanwhile, the persistence of pollutant CO in Shahr-e-Rey station compared to otherstations is the least. Manuscript profile -
Open Access Article
10 - Land use / land cover change modelling using Markov chain and Cellular Automata (Case study: Hamedan province)
Jalil Imani Harsini Mohammad kaboli Jahangir Feghhi Ali TaherzadehBackground and Objective: The extent of spread and source degradation would be determined using prediction of land use/ land cover changes. In this way these changes would be guided in the right directions. The aim of this study is modeling the process of land use / lan MoreBackground and Objective: The extent of spread and source degradation would be determined using prediction of land use/ land cover changes. In this way these changes would be guided in the right directions. The aim of this study is modeling the process of land use / land cover changes of Hamedan province using Landsat TM satellite image of 1989 and IRS LISS III image of 2008. Method: After running the necessary corrections, land use/ land cover maps of the study area in the past two years were obtained using supervised classification with maximum likelihood algorithm. Then probability matrix of land use transition (to each other) were calculated using Markov chain with respect to land use/ land cover map. In the next step, Cellular Automata method was used to geo specified these changes. Findings: Finally land use/ land cover map of Hamedan province for 19 years later (2024) was obtained and the area of each land use/ land cover was calculated. Discussion and Counclusion: The results of this research shows that natural land use/ land covers will be decreased and transmited to human land uses in future. These changes are conceivable due to population growth and increasing human needs to exploit the nature; but this process should be considered to exploit the natural resources in a sustainable manner to avoid severe consequences in future. Manuscript profile -
Open Access Article
11 - Investigation of the role of macroeconomic variables in Tehran Stock Exchange uncertainty using risk filtering, MCMC simulation and ARDL approaches.
Amir Sarabadani Ali Baghani mohsen hamidian Ghodratollah Emamverdi Norooz NoroolahzadehAbstractIn the present study a new total uncertainty criterion in Tehran Stock Exchange was estimated and the impact of macroeconomic variables on this uncertainty was addressed. Risk filtering with an approach to GDFM was first used to detect specific component of 25 t MoreAbstractIn the present study a new total uncertainty criterion in Tehran Stock Exchange was estimated and the impact of macroeconomic variables on this uncertainty was addressed. Risk filtering with an approach to GDFM was first used to detect specific component of 25 time series of the main indices of the Tehran Stock Exchange over 10 years. In the next step, the conditional volatility of the remaining time series’ specific components were estimated using Stochastic volatility (SV) model and finally conditional volatility simulated using Markov chain Monte Carlo (MCMC) approach was averaged to obtain total uncertainty of the Tehran Stock exchange. The ARDL results showed that Tehran Stock Exchange uncertainty is dependent on independent variables such as inflation rate, banks' real interest rate, exchange rate in free Exchange market, liquidity, tax revenue and oil price. According to the results, however, no significant correlation exists between unemployment rate and stock market uncertainty. Manuscript profile -
Open Access Article
12 - Monte Carlo Markov chain simulation under Bayesian inference to identify the parameters affecting earning quality measurement
Hamid Farhadi Fazel Mohammadi Nodeh Seyed Reza Seyed Nejad FahimThe purpose of this research is Monte Carlo Markov chain simulation under Bayesian inference to identify the parameters affecting earning quality measurement. In this regard, in order to predict the earning behavior of companies and to derive the exact parameters of the MoreThe purpose of this research is Monte Carlo Markov chain simulation under Bayesian inference to identify the parameters affecting earning quality measurement. In this regard, in order to predict the earning behavior of companies and to derive the exact parameters of the model from the Bayesian Markov Monte Carlo (MCMC) technique, which takes cross-sectional heterogeneity into account, an analysis was done by coding in Python. In this research, the earning signals extracted from the financial statements on a quarterly basis for a period of 5 years (2018-2022), for 104 companies admitted to the Tehran Stock Exchange, were collected and analyzed using a new measure of earning quality. Auxiliary variables of accounting comparability, financial leverage, operating cycle, and sales volatility were used to achieve more accurate results, and several statistical performance measures (R2, RMSE, and MSE) were used to evaluate the effectiveness of Bayesian-based forecasting models. The results showed that the proposed criterion of the present study derived from the Bayesian model for training and testing data is well able to predict the quality of earning. The evidence shows that the results of the proposed model are superior to the conventional accrual earning management model, which suggests an error rate of MSE=0.0188 and RMSE=0.1369, respectively. The results of the present research can be used to analyze the portfolio and predict the quality of future earnings of companies using historical data. It can also be used to study factors affecting investment performance. Manuscript profile -
Open Access Article
13 - Surveying of the past, present, and future of vegetation changes in the central Alborz ranges in relation to climate change
Diana Askarizadeh Hosein Arzani Mohammad Jafary Javad Bazrafshan Iain colin PrenticeAcceleration of climate trend change is caused by the swift shift of rangeland conditions that using modern methods of evaluation to them are counted to sustainable management of the rangelands. In order for an investigation of trend change of rangeland vegetation due t MoreAcceleration of climate trend change is caused by the swift shift of rangeland conditions that using modern methods of evaluation to them are counted to sustainable management of the rangelands. In order for an investigation of trend change of rangeland vegetation due to climate change, central Alborz rangelands were selected. Normalized Difference Vegetation Index (NDVI) for the period of 30-year (1987-2016) was extracted by Landsat satellite, TM, ETM+, and OLI series. Drought periods were determined using the Standardized Precipitation Index (SPI). The Markov Chain model was used to anticipate the future changes of rangeland vegetation. The results showed that the vegetation cover index’s changes have risen and fallen for three decades in which, despite of increasing for some years 1986 (0.86), 2002 (0.87), 2005 (0.87), and 2015 (0.86); the changes trend was decreasingly for 1995 (0.53), 1998 (0.65), 2000 (0.62), and 2008 (0.61) years, especially for fair to very poor classes. The highest correlation (91.5%) between the SPI and NDVI was shown that severe to moderate drought has taken place along with decreased vegetation periods. Moreover, the Markov Chain model has anticipated a forcible declined change of vegetation cover for 2031 and 2046 periods. Therefore, range management approaches have to prepare itself in order to the gradual increase of temperature, which has destructive effects on vegetation cover, via regulating of grazing capacity and replacing of highly performance livestock in the future. Manuscript profile -
Open Access Article
14 - Modeling land cover changes in Golestan province using land change modeler (LCM)
Fatemeh Salarian Mohammadreza Tatian Abdolazim Ghanghermeh Reza TamartashBackground and Objective In recent decades, land use change due to environmental and human factors has caused serious effects on the environment and the economy in Golestan province. On the other hand, wide rangelands and natural areas have been cultivated without obser MoreBackground and Objective In recent decades, land use change due to environmental and human factors has caused serious effects on the environment and the economy in Golestan province. On the other hand, wide rangelands and natural areas have been cultivated without observing ecological and scientific principles or have been exploited for special purposes and changing to other uses, while many of these lands are do not have the potential to become new land uses and they have a high potential for erosion, as a result of which we will see soil erosion, especially in sloping lands and the creation of destroyer floods. Therefore, it is necessary and essential to be aware of the type and manner of use and its possible changes over time, which will be important for planning and policy-making in the country. The aim of this study was to detection the land use changes in Golestan province during the years 1986 to 2019 and to predict the land use status of the region for 2050 using the Land Change Modeling (LCM) approach.Materials and Methods In order to monitor the trend of land use changes in the study area, Landsat 5 and 8 satellites (TM and OLI sensors for 1986, 2001, and 2019) were used. Interpretation and processing of satellite data were performed in ENVI software. The necessary pre-processing was performed on the images. First, the images were mosaic together and then cut according to the province boundary. In order to identify and separate the phenomena from each other, a false color image was created. Then, the supervised classification method with the maximum likelihood method was used. At this stage, five classes, including rangeland, agriculture, forestry, residential, and water areas were defined. Land use maps for 1986, 2001, and 2019 were prepared. Integration of land cover maps related to 1986, 2001, and 2019 was used as input of LCM model and digital elevation model (DEM) maps and road and stream layers to analyze area changes and prediction of land use changes of 2050. After the necessary analyzes in order to detect land use changes between the intended time periods, change maps and land use transfers were prepared. Finally, the amount of decrease and increase in each land use, the amount of net changes, the net change from other land uses to the desired class, areas without change and transfer from each land use to another land in different land cover classes in the form of maps and charts were prepared and analyzed.Results and Discussion The aim of this study was prediction and modeling of land use changes in a period of 33-years in Golestan province. According to the results during this period, the area of the rangelands has decreased a lot, equivalent to 181181.25 hectares. Much of the decline in rangelands is due to its conversion into agricultural, which can be attributed to population growth and the need to expand crop land. The area of forest lands during the mentioned years has decreased from 393018.75 to 349143.75 hectares in 2019, which has shown a decrease of 43875 hectares (2.2%). In general, the destruction of rangeland and forest areas is especially visible in developing countries due to population growth, technological growth and non-compliance with ecological principles and law enforcement. Also, the results of classified maps during the mentioned years show that the highest amount of changes in the region is related to agricultural lands, has increased to 173700 hectares equal to 8.5 % during the same period. The rate of land use changes related to the residential land class has also increased with the increasing trend from 18731.25 hectares in 1986 to 37518.75 hectares in 2019, which has increased by 18787.50 hectares (0.9%) during this period. Rapid growth of population has led to the development of residential and urban areas and the increase in this type of land use with a relatively steep slope, especially in recent years, which can be part of the government's plans for housing construction in the surrounding areas cities. This increase in the class of agricultural lands is more noticeable, especially in the central and eastern regions of the province, and can be a warning alarm for the future. It means that in an imperceptible trend, rangeland and forest lands become rainfed agricultural lands and after a while unprincipled exploitation, eventually become barren and unusable land. On the other hand, this could indicate an increase in population and demand for housing, and consequently securance of the needs of the residents of the region is a threat to rangeland lands which is necessary instead of increasing the agricultural and residential lands and turning rangeland lands into such land uses, the policy of increasing productivity in the agricultural sector should be pursued. About of water areas, it can be said that during this period, it has increased by 1.6% or 3268.75 hectares. This increase in water areas can be partly attributed to heavy rainfall and water intake and even floods in different parts of the province in 2019. Predicting the rate of land use change in 2050 indicates that in the coming years, the area of rangelands and forests will be reduced by 131906.25 and 291600 hectares, respectively, and in contrast to the area of agricultural land and residential areas will increase to 164137.50 and 25313.25 hectares, respectively. Therefore, the adoption of necessary measures and policies to further reduce forest and rangeland will be inevitable.Conclusion Understanding of the conditions of different land uses during the coming periods will facilitate planning for the future by creating information in terms of their spatial distribution pattern, but maintaining and creating sustainable conditions for the future both statistically and it is ecologically one of its limitations. These constraints play an important role in the safe use of different land uses in the planning process. Therefore, creating sustainable conditions in the region and modeling it in order to use the natural resources of a region regularly and sustainably is one of the preconditions for achieving upstream visions and documents, including the sustainable development plan. Manuscript profile -
Open Access Article
15 - Investigation of forest area using support vector machine and provide a model for predicting the level of changes
Armin Hashemi Amin Khademi Morteza Madanipour Kermanshahi Behrouz KordBackground and Objective Due to the increasing degradation at the level of the natural ecosystem, the amount and location of land use changes and predicting its future growth trend, I can provide the information I need to planners and managers. In this study, in order t MoreBackground and Objective Due to the increasing degradation at the level of the natural ecosystem, the amount and location of land use changes and predicting its future growth trend, I can provide the information I need to planners and managers. In this study, in order to change the current changes and predict the future in the Siahkal range, forecasting and changing the nose were done with Landsat images. There are various methods for predicting land use change. Processes for predicting and modelling land use change, such as urban growth and development, deforestation, etc., are considered powerful tools in managing natural resources and changing the state of the environment. This change reflects how humans interact with their environment, and its modelling has had an impact on settlement and macro-planning. In this research, due to the high capabilities of remote sensing and modelling tools and predicting changes in change using automatic-Markov cells in forests in northern Iran.Materials and Methods In this research, Landsat 5 images, 2000 TM sensor, Landsat 7 ETM+ sensor 2010 and Landsat 8 OLI sensor 2018 are used. In the preprocessing stage, errors in raw data such as radiometric, atmospheric, geometric, etc. errors are corrected. Was significant but had a radiometric error. 84 points are used for forest use, 76 points for thin forest water, 31 points for consumption and 2 required sensitivities to indicate a specific level of land cover. Land cover is defined into five classes: dense forest, semi-dense forest, sparse forest, urban area and agricultural area. The ENVI Remote sensing Software defines four types of kernels for the support vector machine in the SVM classification section: Polynomial, Sigmoid torsion, and FBCTION (RBF). According to the best kernel studies for land use classification, the radial kernel (RBF) has been proposed. In the present study, this kernel was used for classification. The classification of the appropriate band composition that you want to separate these classes for visual interpretation was selected by the spectral mean plot. This is done by the complex OIF index. After the extraction of land uses by the method, the results were evaluated accurately. Maps are prepared by land use, then with the GPS position of the earth, the map of the situation in the visible area and using the formed error matrix of kappa weakness and its overall accuracy obtained for this work, 200 points are randomly created on the images. The use of these points was determined by field visits and topographic maps of the surveying organization. Land use classification models are prepared, for modelling and land use changes are entered into office software to design land use changes in the required years. Degree of land use change modelling The LCM model was used in the Idrisi software environment. The Markov-CA model is a combination of automated cells, Markov chains, and multi-purpose land allocation. The Markov model also shows each user by generating a set of status probability images from the transfer probability matrix. In the last step of the structural model, using the transfer area matrix in the CA Markov model, a simulated simulation of future land use can be obtained. In this research, the land use map of 2010 and 2018 was used to predict the 2028 map. And in order to accurately review the forecast by CA Markov using the user map for 2000 and 2010, the map for 2018 has been predicted and increased by the map obtained from the classified level for this year.Results and Discussion The classification accuracy test was obtained using the Kappa coefficient index and overall accuracy. Kappa coefficient and overall accuracy were 0.88 and 0.89 for the image of 2000, 0.91 and 0.92 for the image of 2010, and 0.93 and 0.95 for the image of 2018, respectively. The images are categorized as entered into the software and processed by changing the LCM. Changes in the LCM model showed that during the years 2000 to 2018, more changes were related to the conversion of semi-dense forest land with an area of 42104.27 hectares. Urban land use change has also increased in the years of many studies and amounted to 148.14 hectares. The table of the probability of land use changes in the Markov production model and with the production map at this stage, for the years of Markov forecast studies for 2018 and 2028 showed that in 2028 the urban class area increased to 21293.1 hectares and the valuable land use area of dense forest to 2189.97 hectares will be reduced.Conclusion In order to prevent the uncontrolled expansion of cities, residential areas and the destruction of forest areas and vegetation, management measures should be taken and management decisions should be made. The level of dense and semi-dense forests in areas with high slopes will decrease further by 2028. Urban land use changes have also increased in the study years and amounted to 148.14 hectares. The results of surveying the area of forecasting classes showed that in 2028, the area of urban classrooms will increase to 21293.1 hectares and the valuable land use area of dense forests will decrease to 2189.97. The ability of the vector machine model in determining land cover/land use, vegetation and forest cover in different regions of Iran has been proven by other researchers. Remote sensing tools can be an important arm in information production in natural resource management. Manuscript profile -
Open Access Article
16 - 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
17 - 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
18 - Oil Price estimating Under Dynamic Economic Models Using Markov Chain Monte Carlo Simulation Approach
Kianoush Fathi Vajargah Hossein Eslami Mofid Abadi Ebrahim Abbasi -
Open Access Article
19 - An Economic Design of Combined Double Sampling and Variable Sample Size X ̅ Control Chart
Saeed Khaki Niloufar Ghanbari Mir Mahdi Seyed Esfehani -
Open Access Article
20 - Optimum Process Adjustment Under Inspection Errors with Considering the Cycle Time of Production and Two Markets for the Sale of Goods
Somayeh Ayeen -
Open Access Article
21 - Discovering and Recovering the Changes in Land Use and Land Cover Using Remote Sensing and GIS (Case Study Heev Village, Alborz Province)
zahra talebi banizi Zahra Naserian Mohammad Mazrae MolaeiDetecting changes is one of the basic needs in the management and evaluation of natural resources. Modeling the process of land cover changes over time using multi- time data in the GIS environment can act as one of the most important factors in managing the mentioned c MoreDetecting changes is one of the basic needs in the management and evaluation of natural resources. Modeling the process of land cover changes over time using multi- time data in the GIS environment can act as one of the most important factors in managing the mentioned changes. In order to modeling the process of land cover changes and to investigating the possibility of predicting it in the future, land change modeling (lcm) has been used. Therefore, the Landsat TM5 analyzer data of Heev village in Alborz province for the years 1985T 2000 and 2011 were analyzed. Next, using the maximum similarity method, land cover maps of each image for the mentioned years, was extracted and categorized into five layers of vegetation, city, asphalt, barren lands (soil) and rocks and cliffs. The extracted accuracy evaluation coefficients (overall accuracy and kappa coefficient) indicate the high accuracy of this classification method. The analysis of the results obtained from the studies conducted on the two periods of 1985-2000 and 2000-2011 shows an increase in urban construction with a decrease in vegetation, and even in some areas, the disappearance of vegetation, while the village is expanding towards the mountainside. Using the combination of Markov model and automatic cell maps land use prediction maps for the next 16 years were obtained, while the kappa coefficient was used to determine the prediction compliance, and comparing them with the actual map Manuscript profile -
Open Access Article
22 - An analytical model for estimating the reliability of critical software systems by considering the self-healing property of bottleneck components
Ali Tarinejad Habib Izadkhah Mohammad Reza MollaHosieni Kamal Mirzaie -
Open Access Article
23 - An Interval Type-2 Fuzzy-Markov Model for Prediction of Urban Air Pollution
Aref Safari Rahil Hosseini Mahdi Mazinani -
Open Access Article
24 - A model for determining optimum process mean in the presence of inspection errors by considering the cycle time
mohammad saber fallah nezhad somayyeh ayeen -
Open Access Article
25 - A Multi Objective Fibonacci Search Based Algorithm for Resource Allocation in PERT Networks
Behrouz Afshar Nadjafi Salman Kolyaei -
Open Access Article
26 - Using Markov Chain to Analyze Production Lines Systems with Layout Constraints
sadegh Abedi morteza mousakhani naser hamidi -
Open Access Article
27 - Forecasting Changes in the Morphology of Sefid Rood River Using Arc GIS
Aghil Madadi Tayebeh Babaei olam Alireza GhodratiConsidering the flood events, especially for the settlements around the rivers, the lack of correct information about the consecutive changes of the river bed and its movement in the coming years is one of the important scientific issues of watershed management, therefo MoreConsidering the flood events, especially for the settlements around the rivers, the lack of correct information about the consecutive changes of the river bed and its movement in the coming years is one of the important scientific issues of watershed management, therefore, due to insufficient information about the behavior of the rivers, the settlements along the rivers in the coastal areas are constantly damaged. The scope of this research is from the border of Konik Kohestan to Jalga. The purpose of this research is to predict the changes in river morphology (channel width and measurement of Pichanroudi and river curvature coefficient) in the coastal areas of the north of the country through the integrated methods of remote sensing with the model of Markov automatic weighing cells. Sefidroud, as the largest and most important river on the southern shores of the Caspian Sea, plays an important role in the life, activities and human capital of the region. The morphological factors of the river and its surroundings and the prediction of future conditions can be effective and necessary in the planning and preparation of coastal plains. In this research, the Landsat 5, 7 and 8 satellite images of 2002, 1987 and 2018, along with the data of changes in the level of the Caspian Sea and Sefidroud Dubai, field surveys and Envi 5.3, ArcGIS 10.4.1 and Idrisi TerrSet software as The research tool was used. First, the probability values of land use conversion in 2018 were obtained based on the integrated model of the Markov chain and automatic cells. The results showed that the integrated model has high precision and accuracy to predict the future pattern. Then, according to the accuracy and accuracy of the model output, the prediction map of land use and river morphology for 2030 was prepared. By fitting the two maps of 2018 and the forecast of 2030, possible changes in the river environment were obtained and analyzed in four areas. Finally, using the data of changes in the level of the Caspian Sea and the annual discharge of the Sefidroud River, the trend of changes and prediction of the model was investigated. The most likely changes are due to man-made facilities. Erosion processes, change of Pichanroodi and flooding in the distance from Sangar Dam to Luman village as lateral displacement of the channel and intensification of Pichanroodi, Kisem village and the city of Astana Ashrafieh and Azadsara to Lichah as flooding of human facilities and in the area of Kiashahr, Bojag wetland and delta Sefidroud is changing the position of the estuary and moving to the west of the river channel, according to the results of the survey of the cross section of the river channel in the three periods of 1987, 2002 and 2018, there has been a decrease in the width of the channel. Manuscript profile -
Open Access Article
28 - برنامه ریزی نیروی انسانی به روش زنجیره مارکوف (مطالعه موردی دانشگاه آزاد اسلامی، واحد فیروزکوه)
ملیحه صحراییمقاله حاضر با هدف پیش بینی و تعیین عرضه خالص نیروی انسانی دانشگاه آزاد اسلامی واحد فیروزکوه برای یک دوره معین انجام شده است. لذا به کمک تجزیه و تحلیل اطلاعات گذشته منابع انسانی، از روش مدل زنجیره مارکوف استفاده شده است و در نهایت تعداد نیروی انسانی، ورود و خروج و همچنین Moreمقاله حاضر با هدف پیش بینی و تعیین عرضه خالص نیروی انسانی دانشگاه آزاد اسلامی واحد فیروزکوه برای یک دوره معین انجام شده است. لذا به کمک تجزیه و تحلیل اطلاعات گذشته منابع انسانی، از روش مدل زنجیره مارکوف استفاده شده است و در نهایت تعداد نیروی انسانی، ورود و خروج و همچنین کمبود و مازاد در هر یک از واحدها و پست های مختلف سازمانی برای 5 سال آینده ( از 1390 تا 1394) پیش بینی شده است و بدین ترتیب تصویر روشنی از وضعیت نیروی انسانی از لحاظ ارتقاء، تنزل، انتقال، استخدام و ترک خدمت کارکنان برای تصمیم گیری مدیران فراهم شده است. جامعه آماری این پژوهش شامل کلیه کارکنان دانشگاه آزاد اسلامی واحد فیروزکوه میباشد. Manuscript profile -
Open Access Article
29 - Fault Tolerance Analysis Among Subscriber Stations in the WiMAX Mesh Network
Mahboubeh Afzali Mahmood Fathi MAjid Harooni Kamalrulnizam Abu BakarThe WiMAX mesh network based IEEE 802.16 standard provides maximum using of the bandwidth channel. Mesh WiMAX network is a promising technology by offering high data rate, broadband wireless access, high quality of service and large coverage area with the low cost of de MoreThe WiMAX mesh network based IEEE 802.16 standard provides maximum using of the bandwidth channel. Mesh WiMAX network is a promising technology by offering high data rate, broadband wireless access, high quality of service and large coverage area with the low cost of deployment. One of the most important issues in the WiMAX network is the failure of subscriber stations due to less power or mobility or etc during the relay multi hop transmission path so that knowing of the fault tolerant parameters such as connection resilience has received much attention recently. In this paper, we propose an analytical framework to estimate the connction availability and connection resilience for one node based on the Continuous Time Markov Chain (CTMC) using multiple back up nodes for the selection of sponsor nodes. The multiple backup sponsor node technique enhances the fault tolerance of network in front of failure of sponsor nodes. We also develop the analytical framework to analyze the connection resilience among subscriber stations in the mesh cluster. Knowing of the connection resilience improves the requirements of succeful transmission. Manuscript profile -
Open Access Article
30 - A Model for Software Rejuvenation Based On Availability Optimization
Zahra Rahmani Ghobadi Hasan Rashidi Sasan Hosseinali Zadeh -
Open Access Article
31 - Providing the Markov chain equation model to reduce temperature prediction errors using the Internet of Things (IOT)
Masoumeh Keshavarz Peiman Keshavarzian Farshid Keynia Vahid Khatibi -
Open Access Article
32 - Enhancing Security on Social Networks with IoT-based Blockchain Hierarchical Structures with Markov Chain
Masoud Moradi Masoud Moradkhani Mohammad Bagher Tavakoli -
Open Access Article
33 - Modeling and Evaluation of Web Services in Mobile Networks using Stochastic Colored Petri Nets
Homayun Motameni Mohammad Vahidpour Babak Shirazi Behnam Barzegar -
Open Access Article
34 - Simulation of Landuse Changes and Urban Dynamics using CA-Markov Hybrid Model Case Study: Maragheh City
Hoshang sarvarIn recent decades, along with urbanization, various models have been used to urban growth prediction. In this regard, Urban models based on the automata technique have emerged under the paradigm of a self-organizing system, with cellular automata (CA) being the simplest MoreIn recent decades, along with urbanization, various models have been used to urban growth prediction. In this regard, Urban models based on the automata technique have emerged under the paradigm of a self-organizing system, with cellular automata (CA) being the simplest but most popular in action What happens to each grid cell is defined by a transition rule or transition rules.If the transition rule requires that the state of a grid cell is only dependent on its state at a previous time step, such a model is called a Markov model, and is not considered a CA model. Cellular automata models have one additional feature: the transition rules operate on cells based on the local neighborhood of those cells. In this research, the spatial expansion of Maragheh city was simulated using Cellular automata- Markov chain hybrid model. Satellite images (Landsat) were used for land cover mapping, urban growth monitoring, and modeling land cover changes. Results represent high efficiency of Cellular automata- Markov chain in the urban spatial growth simulation. In the past three decades,development trend of Maragheh city has been more towards barren lands.According to the output of the model,this trend will continue over the next 17 years. So that, the city will be expended due to the transition of barren lands cells state to urban cells state,and 774 hectares from surrounding barren lands will be converted to urban lands. However, with continue of the previous trend, nearly 417 hectares of good agricultural lands will also change to urban lands. Manuscript profile -
Open Access Article
35 - Measuring the Effective Variables on Urban Expansion and Physical Development Simulation of Hamadan City Using Integrated Model of Cellular automata, Logistic Regression and Markov Chain
Saeid Hajibabaei keramatollah ziari kianoosh zakerhaghighiUrban development and irregular migration of rural population to urban areas are significant phenomena that have damaged agricultural lands, natural landscapes, and public open spaces. This issue doubles the need for informed guidance and spatial organization to better MoreUrban development and irregular migration of rural population to urban areas are significant phenomena that have damaged agricultural lands, natural landscapes, and public open spaces. This issue doubles the need for informed guidance and spatial organization to better understand the processes of urban development for future planning. The present study aimed to evaluate the growth of Hamedan city from 1996 to 2019 and then simulate until 2041. The research method is descriptive-analytical, and the cellular automation model was used to simulate physical development, and logistic regression was applied to analyze the impact of different variables on physical growth and the Markov chain was used to analyze user changes. The validity of Landsat satellite images is also evaluated with respect to the kappa value and acceptable overall accuracy. The results indicate that city center and agricultural land variables with ROC of 0.873 and 0.881, respectively, had the most impact on Hamadan urban growth during the last 23 years. The area of urban areas in 1996 was doubled compared to the year 2011, and almost 2.5 times more than in 2019. On the other hand, population growth increased 1.48 times over the past 23 years. This indicates that the growth rate of urban areas exceeded the population growth rate in Hamadan. The results of the model evaluation indicate that the integrated model is able to provide a precise understanding of urban processes and developments such as evaluating past developments and predicting directions and rates of future physical development. Manuscript profile -
Open Access Article
36 - A two-sided Bernoulli-based CUSUM control chart with autocorrelated observations
S. M. T. Fatemi Ghomi F. Sogandi -
Open Access Article
37 - A time-shared machine repair problem with mixed spares under N-policy
Madhu Jain Chandra Shekhar Shalini Shukla -
Open Access Article
38 - Performance evaluation of the croissant production line with reparable machines
Panagiotis H. Tsarouhas -
Open Access Article
39 - Bayesian change point estimation in Poisson-based control charts
Hassan Assareh Rassoul Noorossana Kerrie L Mengersen -
Open Access Article
40 - Impact of Regional Rangeland Cover Degradation on Increasing Dusty Days in West of Iran
Hamid Nouri mohamad faramarzi seyed hadi sadeghi -
Open Access Article
41 - Design of Credit Risk Assessment Model by Predicting Credit Rating Transfer Using Markov Chain Process
Farid Heidarifar Farhad Hanifi gholamreza zomorodianIn the present study, he presented a statistical sample related to the information of legal and credit customers of Tejarat Bank, accepted in the stock exchange during the years 1398 to 1399. Using factor analysis technique and Delphi method, the variables affecting cre MoreIn the present study, he presented a statistical sample related to the information of legal and credit customers of Tejarat Bank, accepted in the stock exchange during the years 1398 to 1399. Using factor analysis technique and Delphi method, the variables affecting credit risk were selected and entered into the data envelopment analysis model, and the performance scores of law firms were obtained using them, and then ranked by the Fitch Institute model. Performing and using the results to predict the movement of customers in different groups using the Markov chain process. The results of data envelopment analysis indicate that 7 companies were identified as efficient in the financial approach and 12 companies in the combined approach. The results of the Markov chain show that the average probability of stopping at the current rank in 1400 in the financial condition is 46% and in the combined mode is 53%, the average probability of improving the situation of companies is 23% and the average probability of falling is 20%. Manuscript profile -
Open Access Article
42 - Assessing the relationship between financial distress and stock returns using the Monte Carlo Markov chain
Monireh DizajiMonte Carlo Markov chain methods are a set of algorithms for sampling possible distributions based on building a Markov chain with desirable properties. One of the most common Markov Monte Carlo chain algorithms is the Metropolis-Hastings algorithm. Therefore, the purpo MoreMonte Carlo Markov chain methods are a set of algorithms for sampling possible distributions based on building a Markov chain with desirable properties. One of the most common Markov Monte Carlo chain algorithms is the Metropolis-Hastings algorithm. Therefore, the purpose of this study is to evaluate the relationship between financial distress and stock returns using the Metropolis-Hastings algorithm in the Tehran Stock Exchange. For this purpose, 151 companies were selected from the Tehran Stock Exchange in the period 2011 to 2020 using systematic elimination sampling method. R software was used to test the research hypotheses. Altman Z and Olson's score were also used to calculate financial distress. Also, in evaluating the relationship using the Metropolis-Hastings algorithm, two different previous distributions for the research variables were used. The results of the study showed that for Altman's financial distress variable, the accuracy of estimating financial distress was higher with the previous non-informed distribution. For O-Olson's financial helplessness variable, the precision of financial distress was higher with Zelner's previous distribution. Meanwhile, in the previous non-informed distribution, the effect of financial distress was not significant and was significant in Zelner's previous distribution. Manuscript profile -
Open Access Article
43 - The Effect of Exchange Rate Fluctuations on the Stock Return Risk of Mining, Automotive and Cement Index based on the Regime Transmission of Markov
Mehdi Zolfagari Bahram SahabiIn capital market, currency fluctuations impacts on changes in financial asset prices such as stock. However, Considering the importance of The return risk of stock (rather than price) for market participants, the question arises that in addition to the impact of MoreIn capital market, currency fluctuations impacts on changes in financial asset prices such as stock. However, Considering the importance of The return risk of stock (rather than price) for market participants, the question arises that in addition to the impact of exchange rate changes on stock price volatility, does the exchange rate has a significant effect on the risk of the stock returns in periods time of short and long term? And whether this effect is same extent or is different in different states in terms of stock price behavior? To answer these two questions is necessary to extract the return risk of stock in different regimes. Thus, the present study attempted to use parametric models based on Markov-switching approach to extract of the return risk of the selected industry index (automotive, mining, cement) in the two different regimes. After extraction of the risk time series we estimate the effect of exchange rate fluctuations on the industry risk time series by using the econometric model ARDL risk in terms of different regimes. The results showed that time series of the return risk follow from regime transition and have got asymmetric reactions of external shocks. Oslo time series of the industry index return risk significantly effect from exchange rate fluctuations in the short-term and long-term. Manuscript profile -
Open Access Article
44 - Markov Chain Analogue Year Daily Rainfall Model and Pricing of Rainfall Derivatives
Tesfahun Berhane Nurilign Shibabaw Tesfaye Kebede -
Open Access Article
45 - The Lindley-Lindley Distribution: Characterizations, Copula, Properties, Bayesian and Non-Bayesian Estimation
Christophe Chesneau Haitham Yousof G. Hamedani Mohamed Ibrahim -
Open Access Article
46 - AN APPLICATION OF TRAJECTORIES AMBIGUITY IN TWO-STATE MARKOV CHAIN
M. Khodabin
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