Markov

Open Access Article

1 - Model forecasts for inflation and economic growth rate futures approach and Gray Markov method
Mohammad Reza Yavarzadeh Ebrahim Hajiani Amir Nazmi

Accurate 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 More

Accurate 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

2 - Introducing an Early Warning System for High Volatility in Tehran Stock Exchange: Markov Switching GARCH Approach
Younes Nademi Esmaeil Abounoori Zahra Elmi

The goal of this paper is to introduce a new model to predict the high volatility of Tehran Stock Exchange. For do it, a Markov switching GARCH models was modeled. With Estimating this model, the transition probability matrix of two states of high and low volatility, wa More

The goal of this paper is to introduce a new model to predict the high volatility of Tehran Stock Exchange. For do it, a Markov switching GARCH models was modeled. With Estimating this model, the transition probability matrix of two states of high and low volatility, was calculated. Using this matrix, we can forecast the probability of market fluctuations in the each period ahead and we can obtain a suitable model for forecasting high volatility. According to the model selection criteria consist of AIC and BIC, the Markov regime switching GARCH model with GED distribution is the best model for forecasting volatility in Tehran Stock Exchange. Based on this model, in this paper, an Early Warning System has been introduced in Tehran Stock Exchange. This model can be used for policy makers to prevent the occurrence of high volatility and to increase the security of investors in Tehran Stock Exchange. Manuscript profile

Open Access Article

3 - Uncertainty about economic policies and the stock market in Iran based on Markov switching model
Hossein Amiri M. Pirdadeh Beyranvand

One of the factors that investors consider in their decisions is the return on equity. Achieving this return is possible in a situation where economic stability exists. One of the aspects of economic stability is the stability of economic policies that plays an importan More

One of the factors that investors consider in their decisions is the return on equity. Achieving this return is possible in a situation where economic stability exists. One of the aspects of economic stability is the stability of economic policies that plays an important role in the economy of the country. So, if there is uncertainty about economic policies, this uncertainty will unconscious of the economic activists towards future economic developments, and the subsequent owners of the capital will be able to make decisions for the future, including capital and the money market and the capital market will be in trouble. Considering the importance of the issue in this paper, using the Markov Switching Model and applying annual data, we investigate the effect of economic policy uncertainty on the return on Iranian stock market during the period of 1981-2016. In this research, the variables of economic growth rate, inflation rate, unemployment rate, interest rate and liquidity growth rate are used as independent variables. In order to measure economic policy uncertainty, exchange rate fluctuations and government budget deficits are also used. The findings of the paper show that dynamic communication of uncertainty in economic policies and stock market returns is always negative, as the increase in uncertainty in economic policies significantly reduces capital market returns. Also, the relation between stock market returns and the uncertainty of nonlinear economic policies and the uncertainty about the return on capital during a period of high-fluctuation diet is stronger and more stable. Manuscript profile

Open Access Article

4 - Investigating the effects of financial development, economic stability and efficiency of cooperative contracts of banks during recession and prosperity
Mohsen mirzasaf Marjan Damankeshideh manizheh hadinejad alireza daghighi mohammadreza mirzaeinejad

10.30495/jfksa.2023.22388

Financial development and stability and their relationship with economic growth are important and influential issues on economic growth. Therefore, economic experts have investigated this issue in many researches by applying various conditions. The purpose of this resea More

Financial development and stability and their relationship with economic growth are important and influential issues on economic growth. Therefore, economic experts have investigated this issue in many researches by applying various conditions. The purpose of this research is to investigate the effects of financial development, economic stability and efficiency of government cooperative contracts during recession and prosperity, which done by applying the Markov switching regime change approach based on the annual data of Iran's economy during the period of 2016-2018. The results of the model estimation show that the variables of financial and oil crises, economic and financial risk, inflation in both periods of prosperity and recession have a negative effect on the efficiency of cooperative contracts. The results show the probability of transition from one regime to another regime and the duration of the regime, if Iran's economy is in a recession at time t, it will remain in the same state despite economic and financial risks and financial and oil crises. Also, there is a 0.80 probability that Iran's economy will return to the state of recession due to other factors. The amount of exposure of Iran's economy to the period of stagnation in the current research is 21 periods against 9 periods of prosperity. Manuscript profile

Open Access Article

5 - Comparing of Bayesian Model Selection Based on MCMC Method and Finance Time Series(GARCH Model)
محمدرضا صالحی راد نفیسه حبیب یفرد

By using the time series models, we can analysis financial data(in last and futuretime). In financial discussions, because of heteroskedastic observations, we can notuse the classical time series models.We focus on popular practical models for financial time series, GAR More

By using the time series models, we can analysis financial data(in last and futuretime). In financial discussions, because of heteroskedastic observations, we can notuse the classical time series models.We focus on popular practical models for financial time series, GARCH- typemodels, that were introduced for the first time by Bollerslev(1986). These modelsrepresent a very wide class of heteroskedastic econometric models. Time seriesmodels(GARCH models too), like regression models, have random errors. Theseerrors have specific distributions.Since that, the GARCH models variability is not clear, thus, we use the Bayesianmodel selection methods to estimate the parameters of the model. In this method, byusing the prior distributions on the parameters, we find the posterior distributionwhich has integral. Then, we can inference about the parameters.To explore the role of the posterior distribution, the most powerful technique is touse Markov Chain Monte Carlo (MCMC) computing methods such as the Gibbssampler and the Metropolis Hasting (MH) algorithm. These algorithms enable toestimate the posterior distribution, but, they don’t readily lend themselves to estimateaspects of the model probabilities. The most widely used one is the group of directmethods, such as the harmonic mean estimator, importance sampling and bridgesampling. Chib(1995 and 2001) proposed an indirect method for estimating modellikelihoods from Gibbs sampling output. This idea has recently been extended to theoutput of the MH algorithm.We use a reversible jump MCMC strategy for generating samples from the jointposterior distribution based on the standard MH approach. Manuscript profile

Open Access Article

6 - Predicting Index of Stock Exchange by Hidden Markov Model and K-Mean Algorithm
Saeid Asgari Naser Yazdani Mohsen Nazem Bokaei

Stock price prediction is a classic problem that has been analyzed by different tools and models. Stock market trend changes depends on supply and demand rule and other macroeconomic forces in the market circumstance. Non liner and full swing process makes it hard to pr More

Stock price prediction is a classic problem that has been analyzed by different tools and models. Stock market trend changes depends on supply and demand rule and other macroeconomic forces in the market circumstance. Non liner and full swing process makes it hard to predict future stock price. Traditional statistical techniques and models cannot explain seasonal and non-station time series data in stock markets. Hidden markov model has widely used in the way of predicting statistical time series. It extensively has used in such majors as speech recognition and DNA sequencing and also it can be used in order to next stock price prediction. In this study we tried to use discrete hidden markov model to predict next day’s index in Brussels (Euro Next) and answer the question that “which market will get the more accurate prediction by hidden markov model?. Manuscript profile

Open Access Article

7 - Forecasting Petroleum Futures Markets Volatility with GARCH and Markov Regime-Switching GARCH Models
مرتضی بکی حسکوئی فاطمه خواجوند

In 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 More

In 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 White􀀀s Reality Check and Hansen􀀀s 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

8 - The effects of financial stress index on economic growth using linear and nonlinear models (Markov Switching)
M. Ebrahimi Shaghaghi F. Rahnamay Roodposhti M. Ebrahim Maddahi Hashem Nikoomaram Taghi Torabi

The global financial crisis has affected the advanced and developed economies. Iran's economy has been affected, like many other developing countries. In this paper, the effects of financial stress index on economic growth using linear and nonlinear models (Markov Switc More

The global financial crisis has affected the advanced and developed economies. Iran's economy has been affected, like many other developing countries. In this paper, the effects of financial stress index on economic growth using linear and nonlinear models (Markov Switching) has been investigated. In this regard, after the construction of the index, at the beginning defined a production function and the impact of financial stress on economic growth in the rest of the production function variables measured in Linear method. According to the results of financial stress index in the model of the long - term and short – term negative and significant effect on economic growth. The coefficient of this index is 0.02%, which means that with an increase of 1% in the amount of this indicator, the economic growth per capita decreases by 0.20%.So financial stress an obstacle to economic growth and the variables government spending, taxes, and the rate of exchange, which as indications of how to manage the government policies in fiscal, monetary and exchange Optimally utilized. Finally, to test the hypothesis on the nonlinear method of switching Markov model has been used.The results show that, when financial stress is increasing, the effect of uncertainty on financial stress on economic growth is negative Manuscript profile

Open Access Article

9 - Dependency structure between the markets of Iran, Turkey, China and the United Arab Emirates, according the approach of Copula – Markov Switching
S. Mozaffar Mirbargkar Maryam Sohrabi

Studying, and analyzing the dependency structure between the markets at the economic boom and bust have been suggested by the researchers and theorists of different areas. Furthermore, there have been various models to explain the correlation between the financial marke More

Studying, and analyzing the dependency structure between the markets at the economic boom and bust have been suggested by the researchers and theorists of different areas. Furthermore, there have been various models to explain the correlation between the financial markets. Among them, the Copula model has a high ability to recognize the asymmetric dependence structure. The present research is going to study the dependency structure in the financial markets of four countries; Iran, the United Arab Emirates, Turkey and China at the boom and bust cycling in the period of 2014-2017, applying conditional heterogeneity variance model (GARCH), the Markov switching approach, and the Copula functions. The results illustrate that there is an asymmetric structure in every regime, as at the recession time, the correlation between these markets and Iranian market would be higher than the boom time. Manuscript profile

Open Access Article

10 - Modeling Financial return with Markov Time-Varying Mixed Normal GARCH Model
Shirin Alipour Fatemeh Azizzadeh Khosro Manteghi

In previous studies, the normal mixture, as well as the Markov process, were used to model the financial return, separately. In this study, the normal mixture model is extended to the Markov mixture of normals. The mixture weights in every state are considered time-vary More

In previous studies, the normal mixture, as well as the Markov process, were used to model the financial return, separately. In this study, the normal mixture model is extended to the Markov mixture of normals. The mixture weights in every state are considered time-varying and as a function of past observations, so the limit of constant weight assumption is removed. The proposed model is estimated using Bayesian inference and a Gibbs sampling algorithm has been created to compute posterior density. The performance of algorithm is tested with simulation, then a two-state Markov time-varying Mixed Normal-GARCH model (MMN) with one and two components in every state, as well as limited cases (mean zero), were compared by comparison of their likelihood function. Finally, the model is applied to S&P500 and TEPIX daily return and results show that MMN models with two components provide better results than MMN model with one component which is so-called Markov switching GARCH model. Manuscript profile

Open Access Article

11 - Analysis of the the Impact of Symmetric and Asymmetric Shocks of Oil Price on Investor Sentiment in IRAN: Markovs-Switching Approach
Maryam Yosofinezhad Hossein Sharifi-Renani Saeed Daei-Karimzadeh

10.30495/jfksa.2022.19838

According to the special role of oil in the international economy and also the effect fluctuations of this global variable on the performance of financial market and its role in financial dicisions always has been considered by investors.Therefore, the role of oil in th More

According to the special role of oil in the international economy and also the effect fluctuations of this global variable on the performance of financial market and its role in financial dicisions always has been considered by investors.Therefore, the role of oil in the economy is not only for macroeconomic indicators, rather it has affected on the stock market indicators and variables. Also, according to the special role of oil in the economy of Iran and foreign exchange earnings, the stock market can be affected by fluctuations of oil price. Therefore, determining and recognizing the impact of stock price has played a significant role in forcasting and the overall market trend. And it should also be considered important in the level of investor sentiments and desire to invest. One of the components that always fluctuate the investor sentiments is oil price. In countries such as Iran , Which are heavily dependent on oil revenues the effects of oil price fluctuations are also more sever.Considering that the result of oil exports is the entry of currency in to the country and these currencies are used by the government to developthe country.So the exchange rate is one of therelated  categories with investor sentiments.According to the description provided to achieve prosperity and stability development ,studing and recognizing the investor sentiments and the effective factors are special important.Accordingly , in present study using the monthly data for the years from 1391 to 1398 with the approach of markovs swiching  identify the factors affecting the investment.Research results show that fluctuation in oil prices, exchange rate , money supply and consumer price index can be effective on the investor sentiment. Manuscript profile

Open Access Article

12 - Analyze of the dynamics of optimal hedge ratio in the gold coin market: MS-DCC approach
Sanaz Miri Teimur Mohammadi Farhad Ghaffari

In this paper, for the first time ,calculation of optimal hedge ratio for future gold coin contracts has been conflated a multivariate GARCH model (dynamic conditional correlation) with Markov Switching (MS).To this end, we use spot and futures daily prices over the 201 More

In this paper, for the first time ,calculation of optimal hedge ratio for future gold coin contracts has been conflated a multivariate GARCH model (dynamic conditional correlation) with Markov Switching (MS).To this end, we use spot and futures daily prices over the 2017 March through 2018 March in Iran.The results of the Markov regime switching model indicate that the study period is identified under two regimes, which is a regime that reflects the low correlation regime of the futures market and other regime indicating a high correlation on the future market. Furthermore, the optimal hedge ratio of futures contracts are less than 1 and it means the cost of this strategy is less than simple hedge ratio. In general, it can be said that a higher risk prediction under the influence of bad news leads to a transition to a high correlation regime, with the relief of uncertainty, it will be shifted in other regime. In the Economic Analysis of Extreme points of the time series of optimal hedge ratios, results show that among the major fluctuations, the absolute minimum of them is related to 2017 August 25 because of factors such as the transfer of liquidity from the futures market to the stock market at the election in Iran and the 12th of March (the absolute maximum point) because of reasons like managing investors towards secure assets due to fractures in the markets affected by fear of Trump have had dramatic changes in the aforementioned ratio. Manuscript profile

Open Access Article

13 - The impact of gold prices on global exchange rate fluctuations and ounces
behzad fakari Ameneh Anooshehpour Hossein Hossein Abadi

10.30495/jfksa.2022.21089

The impact of gold on other economic and non-economic variables, as well as the impact of gold prices on other financial and investment markets, has made planning and policy-making in this area difficult. One of the common mistakes in the same policy is to consider the More

The impact of gold on other economic and non-economic variables, as well as the impact of gold prices on other financial and investment markets, has made planning and policy-making in this area difficult. One of the common mistakes in the same policy is to consider the degree of impact and the impact of the price of gold on other variables. For this purpose, in this study, using Markov switching method and with daily data from August 2013 to August 1400, excluding non-common days, the main variables affecting the price of gold in Rials were investigated. The results of the study showed that there are two regimes in the study period, the point of separation of these two regimes was the withdrawal of the United States from the UN Security Council. The elasticity of the rial price of gold to the exchange rate fluctuations in the second regime compared to the first regime has increased sixfold. The elasticity of the rial price of gold to the dollar price in the second regime compared to the first regime has increased 1.6 times. The pull of gold prices to exchange rate fluctuations has replaced its pull against the exchange rate in the second regime. According to the results of the study, it is suggested that policy makers in the decision for parallel gold markets, pay attention to its different tendencies to different variables in different regimes Manuscript profile

Open Access Article

14 - Explain the role of financial and economic variables on stock returns With Markov-switching Model
Atefeh Yazdani Varzi erfan Memarian ali nabavi

In the research, Explain the role of financial and economic variables on stock returns With Markov-switching Model.  Based on information collected from the two codal.ir and TSE.ir websites, availability and momentum. contrarian strategies have been dealt with in t More

In the research, Explain the role of financial and economic variables on stock returns With Markov-switching Model.  Based on information collected from the two codal.ir and TSE.ir websites, availability and momentum. contrarian strategies have been dealt with in the market. From among 318 companies from those listed in Tehran Stock Exchange for the period of 2011-2017 and based on restrictions, 108 companies have been selected as research samples.  Then, using various statistical models, three statistical models of autoregressive time series (with no help from auxiliary variable), linear regression, and Markov-switching have been applied. Using the model’s goodness of fit criterion, these three models have been compared and the best one has been selected. Based on selected model, stock trading strategy for the next 12 months has been predicted. To collect data and perform statistical analyses, Excel spread sheet, as well as SPSS and R software packages have been used. According to the findings, from among minor variables (base volume, institutional investment, and free float) and major variables (currency and inflation rates), only three variables from minor types (base volume, institutional investment, and free float) have been effective on stock trading strategy; and, these variables can be used as auxiliary variables to predict return on stock and to specify stock trading strategy in future, as a result. Manuscript profile

Open Access Article

15 - The effect of financial stability and fluctuations in the value of the national currency on the efficiency of Islamic banking, under the switching regime change model
hadi radfar Mohammad Khazri fatemeh zandi bijan safavi

10.30495/jfksa.2023.22618

In this study, we seek to investigate the effect of financial stability and fluctuations in the value of the national currency on the efficiency of Islamic banking in recession and boom regimes. For this purpose, the effect of study variables during the period of 1373 t More

In this study, we seek to investigate the effect of financial stability and fluctuations in the value of the national currency on the efficiency of Islamic banking in recession and boom regimes. For this purpose, the effect of study variables during the period of 1373 to 1400 is investigated by using the rotation model and Markov switching regime change. The estimation results of the model show that the coefficient of financial development is positive in the prosperity regime. The coefficients of the variables of weakening the value of the national currency in both recession and boom regimes, liquidity and global financial and oil crises have also had a negative impact on the yield of bank contracts in the recession regime. The artificial pricing of the exchange rate in the years before the crisis and preventing its adjustment according to economic conditions is one of the main reasons for the recent fluctuations in the value of the national currency. Thus, as the growth of the exchange rate has increased, the policy makers have tried to control the growth of the exchange rate and prevent its increase by reacting more to it. Meanwhile, the reaction to exchange rate deviations has led to a further weakening of the value of the national currency. As the fluctuations in the value of the national currency increase, the amount of investment in the production sector has decreased and the production situation and the efficiency of the contracts have also worsened. Manuscript profile

Open Access Article

16 - An investigation of the effects of foreign exchange market shocks on Tehran stock exchange by Markov regime switching model
عبدالناصر شجاعی محسن خضری تورج بیگی

Several studies have been accomplished  about the relationship between the  exchange rate volatilities and stock market behavior. In theoretical methods, there is no general agreement about the relationship of foreign exchange market and stock market. This pa More

Several studies have been accomplished  about the relationship between the  exchange rate volatilities and stock market behavior. In theoretical methods, there is no general agreement about the relationship of foreign exchange market and stock market. This paper which is based on a two regime MS-EGARCH(1,1) and with using monthly data between 2000 to 2010 intends to investigate this topic. According to estimation results, the first regime is related to variance regime and low average (recession)and the second regime is related to variance and high average (expansion). In average regime and low variance, foreign exchange market shocks had positive effect on stock return variance but it did not have any effect on the level of average return of stock market. But in variance regime and high average it did not have any significant positive effect on the level of variance and the level of stock return average. The above results showed the asymmetrical effects of foreign exchange market shocks on stock return in two stagnation regime and expansion regime. Manuscript profile

Open Access Article

17 - Financial Risk Modeling with Markova Chain
Fraydoon Rahnamay Roodposhti Hamid Vaezi Ashtiani Bahman Esmaeili

Manuscript profile

Open Access Article

18 - Designing ‏and ‏explaining ‏the ‏ranking ‏model ‏and ‏credit ‏rating ‏transfer ‏using ‏data ‏envelopment ‏analysis ‏model ‏and ‏Markov ‏chain
farid heidarifard farhad hanifi gholamreza zomorodian

10.30495/jma.2022.20579

In &rlm;this &rlm;study, &rlm;using &rlm;factor &rlm;analysis &rlm;technique &rlm;and &rlm;Delphi &rlm;method, &rlm;the &rlm;variables &rlm;affecting &rlm;credit &rlm;risk &rlm;were &rlm;selected &rlm;and &rlm;entered &rlm;into &rlm;the &rlm;data &rlm;envelopment &rlm;a More

In &rlm;this &rlm;study, &rlm;using &rlm;factor &rlm;analysis &rlm;technique &rlm;and &rlm;Delphi &rlm;method, &rlm;the &rlm;variables &rlm;affecting &rlm;credit &rlm;risk &rlm;were &rlm;selected &rlm;and &rlm;entered &rlm;into &rlm;the &rlm;data &rlm;envelopment &rlm;analysis &rlm;model, &rlm;and &rlm;the &rlm;efficiency &rlm;scores &rlm;of &rlm;Tejarat &rlm;Bank &rlm;legal &rlm;and &rlm;credit &rlm;companies &rlm;listed &rlm;on &rlm;the &rlm;stock &rlm;exchange &rlm;were &rlm;obtained &rlm;using &rlm;them. &rlm;Then &rlm;the &rlm;ranking &rlm;is &rlm;done &rlm;by &rlm;the &rlm;model &rlm;of &rlm;Fitch &rlm;Institute &rlm;and &rlm;using &rlm;the &rlm;results, &rlm;the &rlm;transfer &rlm;of &rlm;customers &rlm;in &rlm;different &rlm;groups &rlm;is &rlm;predicted &rlm;using &rlm;the &rlm;Markov &rlm;chain &rlm;process. &rlm;The &rlm;results &rlm;of &rlm;data &rlm;envelopment &rlm;analysis &rlm;indicate &rlm;that &rlm;7 &rlm;companies &rlm;were &rlm;identified &rlm;as &rlm;efficient &rlm;in &rlm;the &rlm;financial &rlm;approach &rlm;and &rlm;12 &rlm;companies &rlm;in &rlm;the &rlm;combined &rlm;approach. &rlm;The &rlm;results &rlm;of &rlm;the &rlm;Markov &rlm;chain &rlm;show &rlm;that &rlm;the &rlm;average &rlm;probability &rlm;of &rlm;stopping &rlm;at &rlm;the &rlm;current &rlm;rank &rlm;in &rlm;1400 &rlm;in &rlm;the &rlm;financial &rlm;condition &rlm;is &rlm;46% &rlm;and &rlm;in &rlm;the &rlm;combined &rlm;mode &rlm;is &rlm;53% &rlm;and &rlm;the &rlm;average &rlm;probability &rlm;of &rlm;improvement &rlm;of &rlm;the &rlm;companies &rlm;is &rlm;23% &rlm;and &rlm;the &rlm;average &rlm;probability &rlm;of &rlm;the &rlm;decline &rlm;is &rlm;20%. &rlm;Turns.. Manuscript profile

Open Access Article

19 - Analysis and forecasting of precipitation in the Larestan area by Markov chain.
بهلول Alijani زین العابدین Jafarpoor حیدر Ghaderi

In 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 More

In 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

20 - Research on Tehran’s dry and wet periods using second grade Markov chain Model
پرویز Kerdavani حسین Mohamadi مژگان Afshar

In 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 More

In 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

21 - The analysis and forecasting of climatic fluctuation of khorasan
Alireza Banivaheb

Concerning 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 , More

Concerning 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

22 - Land use changes by using RS and Markov chain technique in the south-west of Tehran
Faezeh Rajabzadeh

Land 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 More

Land 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

23 - Assessment of climate change uncertainty and its effects on the probability of the Jamishan dam inflow frequency
مریم حافظ پرست مودت علی بافکار الهه پناهی

In 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 More

In 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

24 - Prediction of the land use change using markov chain and cellular automata (case study: Roze Chay basin, Uremia)
Farrokh Asadzadeh Kamal Khosravi Aqdam Laleh Parviz Hassan Ramazanpour Nafiseh Yaghmaeian Mahabadi

Land use surveys and investigations are a prerequisite for the study of watersheds, because regional planning is dependent on the awareness about land use type and future changes. As a result, modeling and predicting of land use is essential for land planning and manage More

Land use surveys and investigations are a prerequisite for the study of watersheds, because regional planning is dependent on the awareness about land use type and future changes. As a result, modeling and predicting of land use is essential for land planning and management in the future of a country such as Iran, where land use is changing rapidly In this regard, in order to reveal the land use changes in the 15 years and modeling the changes for the next 20 years, the markovin transmission estimator was used with Landsat 7 and 8 Landsat satellite imagery data from the Roze Chay basin of urmia. Based on the controlled classification algorithm with the maximum probability of land use as seven classes of land uses in this watershed were seven garden, irrigated farming, dry farming, grass land, residential area, water and salt marsh with a mean Kappa coefficient of 0.88 and overall accuracy of 0.9 for 2000 and 2015 were extracted. The changes of 15 years showed that the variation of water dependent uses in the region decreased during the mentioned time period (percentage reduction in the area of agricultural crops and gardens, 32.51). The modeling of land use changes in the region with the markovin transmission estimator suggests that the use of gardens, arable and dry lands, villages and water resources will decrease, and the use of grass land and salt marsh will increase in the region (from 2020 to 2035 percent increase in area grass land 13.11 and the percentage of dry farming 17.56). The results indicate that soil and water resources are used improperly in the studied area, which requires comprehensive planning and management in the watershed. Manuscript profile

Open Access Article

25 - Land use management change in Marvdasht plain - Fars Province
Khatereh Nobaharan Shahla Mahmodi seyad ali abtahi

In 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 More

In 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

26 - 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 Golmohammadi

10.30495/wsrcj.2022.68546.11310

Background 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 More

Background 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

27 - Prediction of meteorological drought conditions in Iran using Markov chain model
Mehdi Ghamghami Javad Bazrafshan

Drought management is very important for optimal water resources application in arid and semi-arid regions. One strategy to manage drought is to predict drought conditions by probabilistic tools. In this study, total monthly precipitation records related to 33 More

Drought management is very important for optimal water resources application in arid and semi-arid regions. One strategy to manage drought is to predict drought conditions by probabilistic tools. In this study, total monthly precipitation records related to 33 synoptic stations of Iran during 1976-2005 were used to monitor and predict future drought conditions. Regarding the dry periods greater than six months in the arid regions of the country, the Standardized Precipitation Index (SPI) at 6-month timescale was used for drought monitoring. The first-order Markov chain model was employed to predict drought condition up to 3-step ahead. This model was fitted on the SPI series at all stations of interest, and it was identified that can represent the probabilistic behavior of drought over Iran. The results obtained from drought prediction at 1, 2, and 3-step ahead over Iran showed that the occurrence of the severe drought (9 percent of stations) or normal conditions (87 percent of stations) is most probable in the future months, regardless of drought condition at current month. Also, drought monitoring based on aerial mean of monthly total precipitation time series over country showed that the trend of drought severity has been increasing in recent years. Manuscript profile

Open Access Article

28 - 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 vafaei

10.22034/jest.2019.44248.4663

Background 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 More

Background 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

29 - Study of Persistence of Polluted Days with Carbon Monoxide (CO) in Tehran City Using Markov Chain Model
Jaber Rahimi Ali Rahimi Javad Bazrafshan

AbstractIntroduction & 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 More

AbstractIntroduction & 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

30 - Land use / land cover change modelling using Markov chain and Cellular Automata (Case study: Hamedan province)
Jalil Imani Harsini Mohammad kaboli Jahangir Feghhi Ali Taherzadeh

10.22034/jest.2017.10333

Background 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 More

Background 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

31 - Forecasting fluctuations of gold coin futures price on Iran mercantile exchange using parametric methods
mohamad esmail fadainejad ali saleabadi gholamhosein asadi mohamad taghi vaziri hasan taati kashani

One of the most important topics in financial markets in recent decades is the forcasting. The main purpose of this study is to forcast volatility future prices.In this research, four groups of symmetric GARCH (GARCH), exponential GARCH, FIGARCH and multi-regime GARCH m More

One of the most important topics in financial markets in recent decades is the forcasting. The main purpose of this study is to forcast volatility future prices.In this research, four groups of symmetric GARCH (GARCH), exponential GARCH, FIGARCH and multi-regime GARCH models have been estimated and forecasted using normal distribution, t-distribution and GED distribution. According to the model error for forecasting fluctuations, the Markov Switching GARCH model (MS-E-GARCH) is reported to be the most efficient model to forecast the fluctuations in the gold coin futures market.The results of the estimation by the Markov Switching GARCH model (MS-E-GARCH) show that fluctuations of gold coin futures market are predictable; and as a result the gold coin futures prices do not have the weak form of efficiency in both low and high volatility settings and systematic profits could be achieved in this market. According to the results of the study, the accuracy of MS-E-GARCH model is higher for GED distribution in comparison with other models. Manuscript profile

Open Access Article

32 - Investigation of Weak Form Efficiency Hypothesis in Both High and Low Volatility Regimes of OPEC Crude Oil Market
mahmood mohammadi alamuti mohammad reza haddadi younes nademi

Crude oil is a strategic commodity that has been one of the largest commodity market over the past 40 years in the world. The main players in the market, such as manufacturers, financial institutions and individual traders are interested in recognizing and benefiting fr More

Crude oil is a strategic commodity that has been one of the largest commodity market over the past 40 years in the world. The main players in the market, such as manufacturers, financial institutions and individual traders are interested in recognizing and benefiting from some moving trends and practices in oil prices and returns. A market where prices always and fully reflect information is called efficient. Thus, there are 3 types of market efficiencies: weak form, semi strong form and strong form efficiency. In research, the weak form efficiency is often tested. In this study, the weak form efficiency of the OPEC crude oil market for daily data during the period from 4 January 2010 to 29 December 2017 by the two mode Markov regime switching GARCH model has been examined and the results of the estimation indicate a lack of efficiency in both high and low volatile regimes of the crude oil market. Manuscript profile

Open Access Article

33 - 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 Noroolahzadeh

AbstractIn 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 More

AbstractIn 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

34 - The Development of Forecasting Model for Coherent Risk in Exchange Companies: Accounting data Approach
Hosein Aryaeinezhad Arash Naderian Hosein Didekhani Ali Khozain

Iran Stock Exchange has developed a lot in recent years. Today, the importance of forecasting and its benefits for decision-making and policy-making from various dimensions, especially in the field of investment, is not hidden from anyone. Risk is one of the first conce More

Iran Stock Exchange has developed a lot in recent years. Today, the importance of forecasting and its benefits for decision-making and policy-making from various dimensions, especially in the field of investment, is not hidden from anyone. Risk is one of the first concerns of investors and is an important criterion in decision making. Value at risk as a risk measure has given way to measuring a variety of risks, but despite the high efficiency of this model due to some shortcomings, including the lack of aggregation feature of a coherent risk measure. Conditional Risk Value (CvaR) is considered as a coherent risk measure that has recently been welcomed and has been proposed as a useful tool for measuring risk.To predict the risk, various models have been presented so far, each of which has its strengths and weaknesses. Some of them are weak in terms of lack of appropriate theoretical foundations and others have not shown proper efficiency in practice despite using appropriate theoretical foundations. Provide adequate empirical risk assessment that helps both investors and anticipate unexpected risks that may threaten companies. In recent years, much attention has been paid to the application of neural network models and hybrid models. In the present study, a combined model of coherent risk prediction is presented and developed using fuzzy neural network inference system (ANFIS) based on Markov switching models and Garch family models. Manuscript profile

Open Access Article

35 - Testing the Fractal Market Hypothesis with the Markov Regime Change Model: A Possible Combination and Convergence
Yaghoub Mahmoudi Shadi Shahverdiani Hamid Reza Kordlouei Mahdi Madanchizaj

The importance of predicting and knowing the future in order to plan and formulate economic strategies is not hidden from anyone. The accuracy of forecasts is one of the most important factors in choosing the type of forecasting method. The stock price index is one of t More

The importance of predicting and knowing the future in order to plan and formulate economic strategies is not hidden from anyone. The accuracy of forecasts is one of the most important factors in choosing the type of forecasting method. The stock price index is one of the effective variables in economic systems that these very complex time series are usually assumed to be random and as a result their changes are assumed to be unpredictable. Such time series variables have the property that the shock to the variable takes a long time to disappear due to the possibility of long-term memory. The aim of the present study was to test the fractal market hypothesis with the Markov regime change model with a possible combination and convergence in the Tehran Stock Exchange. In this paper, the amount of long-term memory and stability of financial time series resulting from the total stock market index for the period 1388-1386 were examined. For this purpose, first the existence of long-term memory was examined, then the fractal nature of the market was examined using the Harst view index. The results indicate the existence of long-term memory in this variable. In this case, with one differentiation, it becomes more differentiated, so the stock price index series in Iran has long-term memory and the effects of each shock on this variable due to its long-term memory remain for long periods. It stays. The results also showed that the overall stock market index is fractal. Manuscript profile

Open Access Article

36 - 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 Fahim

10.30495/jik.2024.23244

The 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 More

The 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

37 - 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 Ghaffari

The 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 More

The 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

38 - The Relation Between one Economic Events with the Concepts of Changing Regime about Returns, Risk and Liquidity in Stock Market
Hassan Ghalibafasl Naser Elahi Masoomeh Torkaman Ahmadi Yadolah Dadgar

The stock market is one of the most important parts of the capital market. There are defined concepts in this market that are more important than the other ones. Meanwhile, it can be mention to liquidity, risk and return. Given the important three variables has tried to More

The stock market is one of the most important parts of the capital market. There are defined concepts in this market that are more important than the other ones. Meanwhile, it can be mention to liquidity, risk and return. Given the important three variables has tried to model know as GARCH regime and Markov regime switching, the relationship between these concepts with the concepts of changing the regime by important economic events in country's history such as article 44 of the constitution is examined. According to the results of three- regime GARCH model, the most important  Article 44 events in the changes of stock return's volatility process regimes has been identified, due to the behavior of institutional investors in low-volatility regimes in comparison with high-volatility liquidity.  Manuscript profile

Open Access Article

39 - Modelling of capital market returns fluctuations for Tehran Price Index Return: MRS-FI-TGARCH and FI-TGARCH models
Hajar Moradian Ali Haghighat Hashem Zare Mehrzad Ebrahimi

The aim of this paper is to expand flexibility of modeling in capital market fluctuations. We achieve the goal by introducing MRS-FITGARCH model for the first time in the world. We use weekly TEPIX changes from 2009 to 2017. The parameters could change through the regim More

The aim of this paper is to expand flexibility of modeling in capital market fluctuations. We achieve the goal by introducing MRS-FITGARCH model for the first time in the world. We use weekly TEPIX changes from 2009 to 2017. The parameters could change through the regimes. Results show that there are two regimes; regime one with high return mean and high return variance and regime two with low return mean and low return variance. Adding asymmetric effects and long memory potential prediction, are the novation of our new model. Valued Negative asymmetric effects coefficient results that bad news effects on the fluctuations were less than good news. It was not to be valued in regime tow and it means, good news and bad news has the symmetric effects in this regime. In regime one, there is unlimited long memory coefficient but in regime two fluctuations effects decreases in hyperbolic rate.   Manuscript profile

Open Access Article

40 - A Comparative Study of the Reflections of Voltaire and Akhundzādeh
Sa‘īd Ganjbakhsh Zamānī

The present article is an analysis of the entrance of the Volterian views from Russia to Caucasia and their impacts on the consideration of Akhundzādeh. Also two works (Candidate by Voltaire and Aallegories by Akhundzādeh) are compared and contrasted.

The present article is an analysis of the entrance of the Volterian views from Russia to Caucasia and their impacts on the consideration of Akhundzādeh. Also two works (Candidate by Voltaire and Aallegories by Akhundzādeh) are compared and contrasted. Manuscript profile

Open Access Article

41 - Improving the Mean Time to Failure of the System with the New Architecture of the Main Node with the Replacement Node of Industrial Wireless Sensor Networks for Monitoring and Control using Markov Model
Ahmadreza Zamani Mohammad Ali Pourmina Ramin Shaghaghi Kandovan

10.30486/mjtd.2022.695924

Manuscript profile

Open Access Article

42 - Honeypot Intrusion Detection System using an Adversarial Reinforcement Learning for Industrial Control Networks
Abbasgholi Pashaei Mohammad Esmaeil Akbari Mina Zolfy Lighvan Asghar Charmin

10.30486/mjtd.2023.1977229.1011

Manuscript profile

Open Access Article

43 - 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 Alibakhshi

Nowadays 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 More

Nowadays 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

44 - 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 Pormanafi

Land 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- More

Land 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

45 - 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 Prentice

Acceleration 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 More

Acceleration 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

46 - Predicting locational trend of land use changes using CA-Markov model (Case study: Safarod Ramsar watershed)
Nahid Salehi Mohammad Reza Ekhtesasi Ali Talebi

Predicting land use changes using satellite imagery is now a useful tool for helping planners in complex situations. The purpose of this study was to detect and predict land use changes during the 28-year period (1986-2014) by CA- Markov model in the Safarood-Ramsar wat More

Predicting land use changes using satellite imagery is now a useful tool for helping planners in complex situations. The purpose of this study was to detect and predict land use changes during the 28-year period (1986-2014) by CA- Markov model in the Safarood-Ramsar watershed of Mazandaran province. In this research, land use and NDVI maps were prepared using Landsat TM (1986), ETM+ (2000) and OLI (2014) satellite images. The accuracy of the CA-Markov model was estimated using the Kappa index of 87%. In order to calibrate the CA-Markov model, the land use map was prepared in 2014, and the Kappa coefficient of the mapping from modeling and user base map (2014) was 82%. The results showed that during the period between 1986 and 2014, the area of forest lands decreased by 10.26% and the total area of residential areas increased by 3.27%. The land use map for the years 2021 and 2028 was predicted by the CA-Markov model. The results showed that during the period 2014-2028, forested lands and rangelands decreased by 4.92% and 1.7%, respectively. Residential areas will increase by 8.04% and the agricultural land will change slightly, indicating the changes in land use to residential land. Manuscript profile

Open Access Article

47 - Three-dimensional calibration of land use changes using the integrated model of Markov chain automatic cell in Gorgan-rud river basin
Mahboobeh Hajibigloo Vahed berdi Sheikh Hadi Memarian Chooghi Bairam komaki

10.30495/girs.2020.674554

Background and ObjectiveLand use/cover changes (LU/LC) are considered as one of the most important issues in natural resource management, sustainable development and the environmental changes on a local, national, regional and global scale. Changing uses into each other More

Background and ObjectiveLand use/cover changes (LU/LC) are considered as one of the most important issues in natural resource management, sustainable development and the environmental changes on a local, national, regional and global scale. Changing uses into each other and changing permissible uses into impermissible uses such as changing agricultural lands into residential regions or changing rangelands into eroded and low-yielding dry farming lands are always considered as importand issues in natural resources. Detection of the patterns of the land use changes and prediction of the changes in the future to carry out suitable planning for optimal utilization of uses in natural resource management reveal the need for modeling spatial and temporal changes of LU/LC. This study aims to assess the efficiency of the integrated model of Markov chain automatic cell (CA-Markov model) in simulation and prediction of spatial and temporal changes of Land use/Land cover (LU/LC) in Gorgan-rud river basin by applying three-dimensional Pentius-Melinus analysis in calibration of land use changes by using three assessment indices of Quantity Disagreement, Allocation Disagreement and Figure of Merit as new indices in the assessment of the accuracy of CA-Markov model. Materials and Methods In this research, the Earth observing sensor images of Landsat-5 Thematic Mapper (TM) and Landsat-8 Operational Land Imager (OLI) acquired from the U.S. geographical site dependent on the U.S. Geographical Survey (USGS) were used to predict land use changes by using the integrated model of Markov chain automatic cell in Gorgan-rud river basin. Seven land use classes were separated for Gorgan-rud river basin including forest land class with the use code 1, agricultural land class with the use code 2, rangeland class (a mixture of shrubbery,langeland,agriculture) with the use code 3, water bodies class with the use code 4, barren land class (barren, rangeland, agriculture) with the use code 5, residential and industrial region class with the use code 6, streambed class with the use code 7. In this study, object-oriented classification method and  Support Vector Machine (SVM) algorithm were used to classify Landsat 5 and 8 satellite images and extract the land use classes of Gorgan-rud river basin. Segmentation scale  in this algorithm on a 50 unit scale (SL 50) was selected to classify the satellite images of 1987, 2000, 2009 and 2017. The assessment of the accuracy of Support Vector Machine algorithm in the object-based classification of satellite images was done by representing overall accuracy, Kappa cefficient, user accuracy, producer accuracy, commission error and omission error for four study periods. To understand how the changes in the region were created during the period of the study three decades and which classes had the area expansion and which classes had the area decrease, changes in the limits of the classes were revealed and percent of the changes in each class were obtained by using the classification maps and IDRISI software. CA-Markov model predicts the changes of different groups of LU/LC units based on spatial neighbourhood concept, transition probability matrix. Preparing land suitability maps is necessary to predict land use changes so that spatial changes can be controlled for each use by probability rules via filtering suitability maps. Validation of Markov model was performed by using three-dimensional Pentius-Melinus analysis with three assessment indices of Figure of Merit, Quantity Disagreement and Allocation Disagreement. Results and Discussion Support Vector Machine algorithm in the classification of the land use based on object-oriented showed that the highest rate of commission error and omission error were observed in rangelands and agricultural lands with 19.12 and 18.55 percent respectively in the land use map of the year 2009. The lowest accuracy of the producer with 71.49 percent belongs to the rangeland use class in the land use map of the year 2009 and the lowest use accuracy with 71.45 percent belongs to agricultural land use class in the land use map of the year 2017. In keeping with the obtained results, the highest positive change belongs to the agricultural land use increase and the highest negative changes belong to rangeland and forest land use decrease during the period of three decades from 1987 to 2017. The highest forest land decrease with 4.8 percent, the highest agricultural land increase with 5.3 percent, the highest rangeland decrease with 9 percent, the highest barren land increase with 4.6 percent and the highest residential and industrial land increase with 0.8 happened during the periods of 2000-2017, 1987-2017, 2009-2017, 2009-2017, and 1987-2017 respectively. After validating the predicted land use chnges in CA-Markov model, based on the analysis of the 5 existing states in three-dimensional Pentius-Melinus analysis, the CA-Markov model with the accurate prediction of simulation of 89.92 percent showed the high efficiency of CA-Markov model in simulation process. After the implementation of the CA-Markov model analysis on the obtained land use map from the classification of the satellite images, one transition probability matrix and one transitioned area matrix were created. In predictions made by using CA-Markov model in 2017 to 2033, the most changes relate to barren and forest land expansion decrease to 16966 and 6961 hectare respectively and in contrast to the use decrease, rangeland, residential and agricultural land expansion increase will be observed to 20397, 3913 and 3825 hectare respectively. Conclusion Detecting land use changes by using LCM tool for the period of three decades 1987-2017 in Gorgan-rud river basin showed that the forest, agricultural and residential use has had significant changes in this region. The obtained results of the prediction of the land use changes during the coming eighteen years by using the integrated model of Markov chain automatic cell following the detected changes by LCM tool show that we will face extreme deforestation phenomenon in this area. Investigation of the obtained results from the implementation of the future use network model by using Markov transition estimator showed that the future use changes can be predicted based on the existing environmental conditions showing that the agriculture will extremely increase in Gorgan-rud river basin during the coming eighteen years. Thus we can protect water and soil resources with comprehensive and long-term management and prevent the degradation of these valuable resources. Three indices of Quantity Disagreement, Allocation Disagreement and Figure of Merit in three-dimensional Pentius-Melinus analysis had an important role in representation of the accuracy rate and calibration of the land use classification and the land use prediction corresponding with the obtained results from the carried out studies concerning the accuracy assessment with indices of Quantity Disagreement, Allocation Disagreement and Figure of Merit. The results of the studied land use changes by using LCM tool and the integrated model of Markov chain automatic cell during the period of 1987 to 2035 show the degradation of more than 24309 hectare of the forest lands and agriculture increase in an area about 62421 hectare indicating human interfernces and deforestation we face in this area. Manuscript profile

Open Access Article

48 - Monitoring and predicting the trend of changing rangelands using Satelite images and CA-Markov model (Case study: Noor-rood basin, Mazandaran proince)
Nematollah Koohestani Shafagh Rastgar Ghodratollah Heidari Shaban Shatai Joybari Hamid Amirnejad

10.30495/girs.2020.674923

Predicting the trend of land use/land cover chenges in natural range ecosystem via remote sensing techniques and evaluating their potentials by modeling, plays an important role in decision making. The goal of this research is monitoring and predicting land use/land cov More

Predicting the trend of land use/land cover chenges in natural range ecosystem via remote sensing techniques and evaluating their potentials by modeling, plays an important role in decision making. The goal of this research is monitoring and predicting land use/land cover changes in Nour-rood basin by CA-Markov in a 60 year periods (1988-2048). Landsat TM (1988, 1998, 2008) and OLI (2018) imagery of similar months (in July) were classified by maximum likelihood method algorithm. Terrestrial reality derived from topographic at scale 1:25000 and aerial photos available in the (GDNR) and (WMM) during 1988-2008 and field visits (2018) were evaluated for accuracy. The accuracy of the production maps calculated with Kappa coefficient. So that the highest and lowest ratio were related to the images of 1998 and 1988, respectively with the values of 0.86 and 0.81. The results were compared with field ground truth to determine the accuracy of results. Random matric used to convert land use classes and the map of land cover of Nour-rud basin predicted, in (2018-2028). The results showed that in (1988-2018), forests and rangelands with excellent and fair cover conditions had decreasing and ranges with good condition, rocks and residential areas had increasing trend. Total area of rangelands decreased from 116206 hectares in 1988 to 106336 hectares in 2018. Moreover, the results of Markov model with more than 85% precision showed the same trend of land use changes from 2018-2048. Excellent rangeland cover conditions, showed decreasing trend, rocky and residential areas will also have an increasing trend until 2048. Markov's prediction model also shows an accuracy of more than 85%. The trend of land use changes during 2018-2048 will be the same as in previous. In whitch case, excellent range condition will have decreasing trend; rocky and residential areas will have an increasing trend until 2048. Manuscript profile

Open Access Article

49 - Modeling land cover changes in Golestan province using land change modeler (LCM)
Fatemeh Salarian Mohammadreza Tatian Abdolazim Ghanghermeh Reza Tamartash

10.30495/girs.2021.681267

Background 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 More

Background 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

50 - 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 Kord

10.30495/girs.2022.684478

Background 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 More

Background 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

51 - 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 Mahini

In 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 More

In 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

52 - Land use change modeling using artificial neural network and markov chain (Case study: Middle Coastal of Bushehr Province)
Mehdi Gholamalifard Mohsen Mirzayi Sharif Joorabian Shooshtari

Coastal 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 More

Coastal 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

53 - 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 Komaki

Monitoring 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 More

Monitoring 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

54 - Structural and Crack Parameter Identification on Structures Using Observer Kalman Filter Identification/Eigen System Realization Algorithm
P Nandakumar J Jacob

10.22034/jsm.2020.1875643.1475

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Open Access Article

55 - Oil Price estimating Under Dynamic Economic Models Using Markov Chain Monte Carlo Simulation Approach
Kianoush Fathi Vajargah Hossein Eslami Mofid Abadi Ebrahim Abbasi

10.22034/amfa.2020.1902265.1446

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Open Access Article

56 - The improved Semi-parametric Markov switching models for predicting Stocks Prices
Hossein Naderi Mehrdad Ghanbari Babak Jamshidi Navid Arash Nademi

10.22034/amfa.2021.1923297.1565

The modelling of strategies for buying and selling in Stock Market Investment have been the object of numerous advances and uses in economic studies, both theoretically and empirically. One of the popular models in economic studies is applying the Semi-parametric Markov More

The modelling of strategies for buying and selling in Stock Market Investment have been the object of numerous advances and uses in economic studies, both theoretically and empirically. One of the popular models in economic studies is applying the Semi-parametric Markov Switching models for forecasting the time series observations based on stock prices. The Semi-parametric Markov Switching models for these models are a class of popular methods that have been used extensively by researchers to increase the accuracy of fitting processes. The main part of these models is based on kernel and core functions. Despite of existence of many kernel and core functions that are capable in applications for forecasting the stock prices, there is a widely use of Gaussian kernel and exponential core function in these models. But there is a question if other types of kernel and core functions can be used in these models. This paper tries to introduce the other kernel and core functions can be offered for good fitting of the financial data. We first test three popular kernel and four core functions to find the best one and then offer the new strategy of buying and selling stocks by the best selection on these functions for real data. Manuscript profile

Open Access Article

57 - Investigating the Effect of Developing Financial Institutions on Economic Growth with Panel Vector Autoregressive Approach and Markov Switching Approach in MENA Member Countries
Marjan Habibollahi Reza Maaboudi Mohammad Khorsand

10.22034/amfa.2022.1962118.1770

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Open Access Article

58 - Investigation of Markov Dynamic General Equilibrium Marking Model (MS-DSGE) in order to Develop Iran's Monetary-Economic System
Mohammad Ghasemi Kiomars Soheili Shahram Fattahi

10.30495/jsm.2022.1971216.1697

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Open Access Article

59 - An Economic Design of Combined Double Sampling and Variable Sample Size X ̅ Control Chart
Saeed Khaki Niloufar Ghanbari Mir Mahdi Seyed Esfehani

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Open Access Article

60 - Optimum Process Adjustment Under Inspection Errors with Considering the Cycle Time of Production and Two Markets for the Sale of Goods
Somayeh Ayeen

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Open Access Article

61 - Detecting and predicting vegetation cover changes using sentinel 2Data (A Case Study: Andika Region)
sedigheh emami esmail emami

The earth surface is itself a complex system, and land cover variation is a complexprocess influenced by the interference of variables. In this study, the data of Sentinel 2for 2017 and 2016 were processed and classified to study the changes in the Andikaarea. After dis More

The earth surface is itself a complex system, and land cover variation is a complexprocess influenced by the interference of variables. In this study, the data of Sentinel 2for 2017 and 2016 were processed and classified to study the changes in the Andikaarea. After discovering vegetation changes between two images over the mentionedtime, vegetation increased by 661.74 hectares. Multiple regressions have been used toidentify factors affecting vegetation changes. Multiple regressions can explain therelationship between vegetation changes and the factors affecting them. In order toinvestigate the factors affecting vegetation change, altitude data, distance from theroad, distance from residential areas of the village and river were introduced intoregression equation. Since this method uses three parameters such as Pseudo-R2 andRelative Operation Characteristic (ROC(, 0.23, and 0.696 values for the aboveparameters, which indicates that the model is in good agreement. The results ofregression analysis show that linear composition of height variable as independentvariables in comparison with other parameters has been able to estimate vegetationchange. Subsequently, by using two classified pictures of 2017 and 2016, the amountof vegetation changes was calculated, and Markov chain method was used for 2018forecast changes. Manuscript profile

Open Access Article

62 - Predicting Land Changes in River Margin and Urban Areas by Remote Sensing and GIS
ehsan izadi Ali Akbar Jamali

Today, the rapid growth of the world's urban population, especially in developing countries, hascreated many problems in various fields. Among these, land-use change is of great importance.Modeling and predicting future land-use changes has become increasingly important More

Today, the rapid growth of the world's urban population, especially in developing countries, hascreated many problems in various fields. Among these, land-use change is of great importance.Modeling and predicting future land-use changes has become increasingly important for urban andenvironmental management and other relevant authorities and researchers. The main purpose of thisstudy is to apply cellular automata (CA) Markov models based on spatial information system tosimulate and predict land-use change. Landsat satellite imagery was prepared during the three periodsof late June 1986, 2001, and 2016. Then land use maps of the study area were obtained by classifyingthe maps. The model derived from the CA Markov was implemented to predict and process and toanalyze land-use changes by 2031. Forecast results showed that from 2016 to 2031, green space, urbanresidential land use increased and the agricultural and open land use declined. This study will generallyshow the decline in open land and agriculture and the expansion of residential and urban areas in 2031,which was caused by the loss of agricultural land and vegetation. The region's economy, based onagricultural and livestock production will face the current productivity situation in 2031. Manuscript profile

Open Access Article

63 - 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 Molaei

Detecting 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 More

Detecting 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

64 - Monitoring of land use changes in Shahmirzad city using remote sensing data and spatial information system
amir kamalifard

In order to study urban development and land use changes in subsequent periods, we also obtained land use maps and land survey data from Landsat satellite imagery and land use studies in Shahmirzad city to achieve this. Important software is ENVI 5.3, ARC.GIS10.5 and Te More

In order to study urban development and land use changes in subsequent periods, we also obtained land use maps and land survey data from Landsat satellite imagery and land use studies in Shahmirzad city to achieve this. Important software is ENVI 5.3, ARC.GIS10.5 and Terrset. . The results show that over the years studied, the area of horticultural, waste land has declined, and residential and human-made land use has increased. It was 2855094 square meters in 2009 and 2429144 square meters in 2019, following a downward trend. Residential and man-made land in 1999 was 360623 square meters, in 2009 it was 1264976 square meters and in 2019 it was 2495357 square meters, indicating a significant increase. . The change detection revealed that most land use conversions in 1999-2009 were related to conversion of arable land to wastewater by about 20% and from 2009 to 2019 related to conversion of arable land into residential land. With about 16%. Survey results show that in the first 10 years, about 20% of the horticultural land has become waste land and in the second 10 years about 7% of the land has become residential and human-made. Validation of the model with a kappa coefficient of 0.76 indicates that the model may have weaknesses but has acceptable ability to predict changes in the region. Manuscript profile

Open Access Article

65 - 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 Soukhtezari

Land 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 More

Land 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

66 - Prediction of Urban Construction Changes Using Satellite Images Based on CA-MARKOV Models (case study: Sari)
Sahab Bidgoli Kashani Mehran Fadavi Valiollah Azizifar

Along 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 More

Along 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

67 - 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

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68 - Joint Inspecting Interval Optimization and Redundancy Allocation Problem Optimization for Cold-Standby Systems with Non-Identical Components
Mani Sharifi

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69 - An Interval Type-2 Fuzzy-Markov Model for Prediction of Urban Air Pollution
Aref Safari Rahil Hosseini Mahdi Mazinani

10.22094/jcr.2023.1983189.1297

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70 - Cluster-Based Image Segmentation Using Fuzzy Markov Random Field
Peyman Rasouli Mohammad Reza Meybodi

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71 - MHIDCA: Multi Level Hybrid Intrusion Detection and Continuous Authentication for MANET Security
Soheila Mirzagholi Karim Faez

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72 - Utilizing Generalized Learning Automata for Finding Optimal Policies in MMDPs
Samaneh Assar Behrooz Masoumi

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73 - An Adaptive Approach to Increase Accuracy of Forward Algorithm for Solving Evaluation Problems on Unstable Statistical Data Set
Omid SojodiShijani Nader Rezazadeh

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74 - Abnormality Detection in a Landing Operation Using Hidden Markov Model
Hasan Keyghobadi Alireza Seyedin

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75 - Monte Carlo Simulation to Compare Markovian and Neural Network Models for Reliability Assessment in Multiple AGV Manufacturing System
Hamed Fazlollahtabar Mohamma Saidi-Mehrabad

10.22094/joie.2016.190

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76 - Availability analysis of a cooking oil production line
Afshin Yaghoubi Saeed Rahimi Roya Soltani Seyed Taghi Akhavan Niaki

10.22094/joie.2020.1889992.1712

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77 - Exact equations for the reliability and mean time to failure of 1-out-of-n cold-standby system with imperfect switching
Seyed Taghi Akhavan Niaki Afshin Yaghoubi

10.22094/joie.2020.1905939.1773

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78 - A model for determining optimum process mean in the presence of inspection errors by considering the cycle time
mohammad saber fallah nezhad somayyeh ayeen

10.22094/joie.2022.545.45

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79 - Absorbing Markov Chain Models to Determine Optimum Process Target Levels in Production Systems with Rework and Scrapping
Mohammad Saber Fallah Nezhad Seyed Taghi Akhavan Niaki

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80 - A Multi Objective Fibonacci Search Based Algorithm for Resource Allocation in PERT Networks
Behrouz Afshar Nadjafi Salman Kolyaei

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81 - Using Markov Chain to Analyze Production Lines Systems with Layout Constraints
sadegh Abedi morteza mousakhani naser hamidi

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82 - Probing the Discriminatory role of Non-Equilibrium effects in the Emergence of Biological Homochirality by Considering Quantum Constraints
Arash Tirandaz

10.30495/ijbbe.2023.1987032.1026

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83 - Markov Characteristics for IFSP and IIFSP
Nan Jiang Wei Li Fei Li Juntao Wang

10.30495/tfss.2022.1961482.1039

As the research object of modern nonlinear science‎, ‎a fractal theory has been an important research‎ ‎content for scholars since it comes into the world‎. ‎Moreover‎, ‎iterated function system (IFS) is a significant research object of fractal theory‎. ‎On the other ha More

As the research object of modern nonlinear science‎, ‎a fractal theory has been an important research‎ ‎content for scholars since it comes into the world‎. ‎Moreover‎, ‎iterated function system (IFS) is a significant research object of fractal theory‎. ‎On the other hand‎, ‎the Markov process plays an important role in the stochastic process‎. ‎In this paper‎, ‎the iterated function system with probability(IFSP) and the infinite function system with‎ ‎probability(IIFSP) are investigated by using interlink‎, ‎period‎, ‎recurrence and some related concepts‎. ‎Then‎, ‎some important properties are obtained‎, ‎such as‎: ‎1‎. ‎The sequence of stochastic variable $\{\zeta_{n},(n\geq 0)\}$‎ ‎is a homogenous Markov chain‎. ‎2‎. ‎The sequence of stochastic variable $\{\zeta_{n},(n\geq 0)\}$ is an irreducible ergodic chain‎. ‎3‎. ‎The distribution of transition probability $ p_{ij}^{(n)}$ based on $n\rightarrow\infty $ is a stationary probability distribution‎. ‎4‎. ‎The state space can be decomposed of the union of the finite(or countable) mutually disjoint subsets‎, ‎which are composed of non-recurrence states and recurrence states respectively‎. Manuscript profile

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84 - Environmental Assessment of Land Use Due to Dust in the Last Three Decades Using Remote Sensing Technique and CA Markov Model Case Study of Ahvaz
Yaha Abdolkarim Nisi mohammadebrahim afifi Marzieh Mogholi

One of the environmental problems is the air pollution index, the most important index of which is the volume of suspended particles in the atmosphere, and in the southern and western cities of the country in recent years has increased significantly. The aim of this stu More

One of the environmental problems is the air pollution index, the most important index of which is the volume of suspended particles in the atmosphere, and in the southern and western cities of the country in recent years has increased significantly. The aim of this study was to monitor land use changes due to fine dust in the last three decades using remote sensing and CA-Markov in Ahvaz. The research method was field-analytical. After conducting preliminary studies and preparing appropriate satellite images, they were analyzed and evaluated with different amounts of educational samples and according to ground surveys. The images used were Landsat 7, 5 and 8 satellite images of 2000, 2010 and 2020, respectively. The classification was performed by artificial neural network method and the accuracy of the classification was evaluated and the prediction map of the study area was prepared using the CA-Markov model. The classification results showed that the lands built in 2000 increased from 10637.34 to 10925.76 hectares in 2010 and its area increased to 288.42 hectares. From 2000 to 2010, the green space increased from 1275.41 hectares to 1279.99, ie 58.4 hectares, due to the planting of hand-planted trees during these years to deal with fine dust. These changes have been decreasing from 2010 to 2020 and its area changes have increased from 1279.99 hectares to 1120.49, ie 159.50 area has been reduced. Manuscript profile

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85 - Investigation of environmental approach in modeling land use change in Babak city using satellite images, multi-criteria evaluation and Markov chain (1997 - 2021)
mohammadebrahim afifi ahmad mangeli meydok ali vakhshori

Abstract In urban areas, population growth has changed the use of agricultural lands to residential, commercial and industrial. These changes have unpleasant consequences for the urban environment, such as reduced vegetation and increased ambient temperature. Therefore, More

Abstract In urban areas, population growth has changed the use of agricultural lands to residential, commercial and industrial. These changes have unpleasant consequences for the urban environment, such as reduced vegetation and increased ambient temperature. Therefore, evaluating the effects of land use change for proper management in urban areas seems necessary. Therefore, the purpose of this study is to investigate the factors affecting the development of Babak city with regard to the category of sustainable urban spatial development from an ecological perspective. For this purpose, using Landsat 2, 7 and 8 multi-time satellite images and object-oriented satellite image processing techniques, land use changes in the period 2021-1997 with emphasis on the spatial expansion of Babak city have been evaluated. For this purpose, the factors affecting the physical development of Babak city were identified based on the research background in the form of 17 indicators and mapped using multivariate evaluation methods based on CLW fuzzy weighted linear combination and by extracting lands prone to future physical development During the years 2021-1997, using the Markov chain automated cell model, the future land use pattern was predicted in the form of an environmental protection approach and in accordance with the principles of sustainable development until 2065. If the results of this study are used, in Future developments of the city will cause the least damage to pasture and green lands Manuscript profile

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86 - Forecasting Changes in the Morphology of Sefid Rood River Using Arc GIS
Aghil Madadi Tayebeh Babaei olam Alireza Ghodrati

Considering 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 More

Considering 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

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87 - برنامه ریزی نیروی انسانی به روش زنجیره مارکوف (مطالعه موردی دانشگاه آزاد اسلامی، واحد فیروزکوه)
ملیحه صحرایی

مقاله 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 More

مقاله 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

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88 - Classification of changes in the length of rainfall-dependent dry periods in Iran
seyed keramat hashemi ana

To study the behavior of dry period lengths, precipitation data were used on a daily scale for 45 synoptic stations in Iran (1985-2017). In order to spatially distribute the dry periods, sequences of 10, 20, 30 and more than 30 days were used and turned into zones. The More

To study the behavior of dry period lengths, precipitation data were used on a daily scale for 45 synoptic stations in Iran (1985-2017). In order to spatially distribute the dry periods, sequences of 10, 20, 30 and more than 30 days were used and turned into zones. The results showed that the highest frequency of long-term dry periods (30 days and more), with 86 events is related to the south-eastern part of Iran and Iranshahr station. The lowest frequency with 3 cases belonged to Rasht station on the southwest coast of the Caspian Sea in northern Iran. The second-order Markov probability distribution was used to evaluate the type of dry period distribution, return continuity and their probability of occurrence. Probability matrix and return period for 10, 20 and 30 day continuities were calculated on a monthly scale and it was determined that June and April were the shortest dry period return periods (18 days) in the arid central and eastern regions of the country with the highest probability of occurrence ( 89%) and the longest return period is related to October and November in the wetlands of the north and northwest coast of the country (338 days) and the lowest probability of occurrence (28%). Manuscript profile

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89 - Asymmetric Effects of Oil Price Shocks on Economic Growth of OPEC and OECD by focusing on Shocks Setting and Regime Changes
Nader Mehregan Mahmood Haghani Younes Salmani

This paper investigate the asymmetric effect of oil price shocks on economic growth in OECD and OPEC countries with emphasis on the setting of shocks and regime changes during 1972-2011. The results indicate that the role of oil price shocks on the development price unc More

This paper investigate the asymmetric effect of oil price shocks on economic growth in OECD and OPEC countries with emphasis on the setting of shocks and regime changes during 1972-2011. The results indicate that the role of oil price shocks on the development price uncertainty is asymmetric in world markets and the shocks formed in this setting have asymmetric effects on the economy in both groups. But, the asymmetry in the OECD countries and the effects of OPEC, are greater. Of course, the impact of shocks increase when occurred after a stable period of oil price. Furthermore, a shock which influences positively a group ( OPEC or OECD), has negative impact on the other group. Manuscript profile

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90 - SPECIFYING the EARLY WARNING MODEL for INFLATION by USING MARKOV SWITCHING APPROACH
Mohsen Mehrara seyed Mohamad Hosein Fatemi

Abstract This research is an application of the dependent models to the regime in order to determining major determinants of inflation in Iran on the base of seasonal data from 1990:3 to 2016:3, Accordingly, the two inflation regimes, high inflation regime (with an ave More

Abstract This research is an application of the dependent models to the regime in order to determining major determinants of inflation in Iran on the base of seasonal data from 1990:3 to 2016:3, Accordingly, the two inflation regimes, high inflation regime (with an average annual rate of 28%) and low inflation regime (with an average annual rate of 12%), are identified and causes of regime transition have been surveyed. The results show the significant impact of liquidity growth and the output gap on inflation in both regimes. On the other hand, inflationary impact of liquidity growth in low inflation regime estimated less than the high inflation regime. The results of the Markov model indicate that liquidity growth and money market disequilibrium are the factors of transmission from low inflation to high inflation regime but these variables do not contain any significant implications for the transition from high inflation to low inflation regime. So according to the results, it can be concluded that the use of monetary expansionary policies in a low inflation regime can be more effective on the production than high inflation regime. Manuscript profile

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91 - Detecting of Turning Points in Business Cycles of Iranian Economy Through Autoregressive Markov Switching Model
kambiz hojabr kiani Alireza moradi

This study was to investigate, turning points in Business Cycles in the economy of Iran using seasonal date during (1981:1-2008:2). To make it practical Autoregressive Markov Switching Model by Hamilton (1989) was used. Today this approach is used in many advanced count More

This study was to investigate, turning points in Business Cycles in the economy of Iran using seasonal date during (1981:1-2008:2). To make it practical Autoregressive Markov Switching Model by Hamilton (1989) was used. Today this approach is used in many advanced countries in order to identify and dating of cycle. Results showed that in that period in three junctures four records happened. The longest records are during [1991:2-1998:2], with the duration of 7 seasons. In addition to that results showed that in under discussion period every time a record happens in countries for about 1.74 seasons. While the appearance of every Boom in under discussion period in the economy of Iran continued 6.66 seasons. Manuscript profile

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92 - Identifying Regime Switching of Stock Market Returns in Iran
Seyed Yahya Abtahi Hamed Nikfetrat

Financial markets tendency to a sudden shift as a result of changes in the investor behavior can lead to the appearance of different regimes of the price and returns in these markets. This paper, the switching behavior of different regimes in Tehran Stock Market will be More

Financial markets tendency to a sudden shift as a result of changes in the investor behavior can lead to the appearance of different regimes of the price and returns in these markets. This paper, the switching behavior of different regimes in Tehran Stock Market will be investigated through returns (TEDPIX) indexation Switching model during 2006-2011. The results represent that there are 3 positions or regimes for this market. One has a negative return average and two others have a positive returns average. Also, the stability of the regimes has a positive but low returns average and the change of other regimes to this one is of high probability in this market. Manuscript profile

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93 - Investigating the Relationship between Inflation Rates and Inflation Uncertainty in Iran by Using Markov-Switching Regression
Ali Hosein Samadi Sharareh Majdzadeh tabatabaee

This paper studies the relation between inflation rates and its uncertainty by using Markov-Switching regression model and monthly data of consumer price index during 1990:01-2012:09 in Iran. Inflation uncertainty is estimated by using Generalized Autoregressive Conditi More

This paper studies the relation between inflation rates and its uncertainty by using Markov-Switching regression model and monthly data of consumer price index during 1990:01-2012:09 in Iran. Inflation uncertainty is estimated by using Generalized Autoregressive Conditional Heteroskedastisity (GARCH) model. The empirical results of Markov Switching Auto Regressive (MSAR) model represent the presence of two clearly differentiated regimes over the entire Sample. The first regime corresponds to a high level inflation rate, low volatility, and the second regime corresponds to low level inflation, high volatility. The use of Markov-Switching Regression Model indicates that the increase of inflation rate will be associated to higher uncertainty according to both regimes.   Manuscript profile

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94 - Redefinition of the Relation between Energy Consumption and Economic Growth in Iran: Markov Switching Approach
A. M. Mozayani A. Esari Arani B. Afsharian A. Rasouli

Abstract The purpose of this study is finding the relationship between energy consumption and economic growth in the industry and transport sector in developed and developing provinces in Iran through Markov switching model during 2000-2010. The results indicate a posi More

Abstract The purpose of this study is finding the relationship between energy consumption and economic growth in the industry and transport sector in developed and developing provinces in Iran through Markov switching model during 2000-2010. The results indicate a positive effect of energy consumption growth on value added growth in industry and transportation both in developed and developing provinces. But, the positive effect of energy consumption will be increased by moving from recession to economic boom phrase. The results imply that the relation between energy consumption and economic growth in transportation sector is more than industry and there is an asymmetric relation between energy consumption and economic growth. Manuscript profile

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95 - Exchange Rate Pass-Through into Import Price in Iran Economy with Emphasis on Volatility of Oil Revenues (Nonlinear Approach)
Mana Mesbahi Hosein Asgharpour Jafar Haghighat Seyed Alireza Kazerooni firooz fallahi

Abstract The main objective of this paper is to investigate the impacts of fundamental variables and volatility of oil revenue (as one of the most important of environment prevailing components in Iran economy) on degree of exchange rate pass through (ERPT) into import More

Abstract The main objective of this paper is to investigate the impacts of fundamental variables and volatility of oil revenue (as one of the most important of environment prevailing components in Iran economy) on degree of exchange rate pass through (ERPT) into import price. For this, Markov-Switching and EGARCH methods were used on the base of data for 1990:3 to 2014:1. The findings indicate that there are two ERPT into import price regimes in Iran economy. The ERPT is more than unitary in both regimes. Also, volatility of oil revenues has asymmetric impacts on ERPTs of regimes in terms of size and sign but it increases ERPT into import price in both regimes. Therefore, managing of volatility of oil revenues and exchange rate changes are suggested. Manuscript profile

Open Access Article

96 - Asymmetric Effects of Monetary Shocks on Real Output in Iran: A Markov-Switching Approach
Hosein Shariri Renani Razieh Salehi Sara Ghobadi

An important issue in macroeconomics is the effect of monetary shocks on macroeconomic variables. How monetary shocks affect the real production in different economic situations such as recession and expansion is vital for policy makings and the effectiveness of the pol More

An important issue in macroeconomics is the effect of monetary shocks on macroeconomic variables. How monetary shocks affect the real production in different economic situations such as recession and expansion is vital for policy makings and the effectiveness of the policies. So, this research tries to test and analyze the asymmetric impacts of monetary shocks on the productions in Iran by using seasonal Time Series Data during 1999-2008 and Markov-Switching model. The results indicate that negative and positive monetary policies in recession and also expansion period have asymmetric effects on domestic production growth. In general, monetary shocks are more effective in recession than expansion.  Manuscript profile

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97 - State Dependent Effects of Monetary Aggregates on Exchange Market Pressure in Iran's Economy
Mohsen Tooti Seyed Yahya Abtahi Jalil Totonchi Zohreh tabatabaeinasab

The purpose of the present study is to investigate the effects of monetary aggregates on exchange market pressure of Iran's economy using quarterly data and during the period of 2001:02- 2021:04. For this purpose, exchange market pressure index has been calculated More

The purpose of the present study is to investigate the effects of monetary aggregates on exchange market pressure of Iran's economy using quarterly data and during the period of 2001:02- 2021:04. For this purpose, exchange market pressure index has been calculated by Edwards (2002) and Kumah (2007) approach; The results show that the exchange market pressure index of Iran's Economy follows a nonlinear pattern. After that, using the unit root test of Lee and Strazisich (2003), which is based on the minimum Lagrange coefficient (LM) test, the time series has been confirmed in terms of the structural break point, and then using by the approach proposed by Lee and Strazisich (2003), the residual of the time series has been extracted. The results of Markov Switching GARCH model indicate that in the low regime of exchange market pressure, the monetary base variable with a coefficient of 0.29 has the greatest effect on the pressure of the Iranian currency market, followed by liquidity and money variables respectively with coefficients 0.06 and 0.01 increase the pressure of the currency market, with the switch of the regime and being in the high regime of exchange market pressure, the variables of monetary base, liquidity and money with the coefficients of 0.88, 0.54 and 0.31 lead to pressure in the currency market, therefore, the application of contractionary monetary policy and control of monetary aggregates should be considered as a strategic point for economic policy makers. Manuscript profile

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98 - Reliability Evaluation of Power System SVC Types Using a Markov Chain
Ali Behdan Bahador Fani Ehsan Adib

Static reactive power compensator (SVC) plays an important role in power system reliability stems. In evaluations of reliability, only reactive power is considered as a constraint network is placed in the SVC Brrsy‌Ha impact on power system reliability evaluation techni More

Static reactive power compensator (SVC) plays an important role in power system reliability stems. In evaluations of reliability, only reactive power is considered as a constraint network is placed in the SVC Brrsy‌Ha impact on power system reliability evaluation techniques are still not considered. This type of SVC, the TCR-FC, TSC and TCR-TSC examined and the information wrong or repair parts of the states of the user. μ) is expressed.This type of SVC, the TCR-FC, TSC and TCR-TSC examine the error occurs and information Halt‌Hay or repair parts used by our participants .Static reactive power compensator (SVC) plays an important role in power system reliability stems. Thus it is clear that λ is a parameter that indicates the error to each component, and μ is a parameter which indicates the service or go into the same circuit components and repair goes wrong. After the static reactive power compensator (SVC) plays an important role in power system reliability. Manuscript profile

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99 - Fault Tolerance Analysis Among Subscriber Stations in the WiMAX Mesh Network
Mahboubeh Afzali Mahmood Fathi MAjid Harooni Kamalrulnizam Abu Bakar

The 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 More

The 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

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100 - Strategies for monitoring environmental changes: monitoring and predicting land-use land-cover (LULC) change (Case study: South Pars special economic zone, Iran)
Sadegh Mokhtarisabet Afsaneh Shahriari

10.30495/jonass.2022.1957004.1040

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101 - A Model for Software Rejuvenation Based On Availability Optimization
Zahra Rahmani Ghobadi Hasan Rashidi Sasan Hosseinali Zadeh

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102 - 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

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103 - Enhancing Security on Social Networks with IoT-based Blockchain Hierarchical Structures with Markov Chain
Masoud Moradi Masoud Moradkhani Mohammad Bagher Tavakoli

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104 - Unsupervised Texture Image Segmentation Using MRFEM Framework
Marzieh Azarian Reza Javidan Mashallah Abbasi Dezfuli

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105 - Modeling and Evaluation of Web Services in Mobile Networks using Stochastic Colored Petri Nets
Homayun Motameni Mohammad Vahidpour Babak Shirazi Behnam Barzegar

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106 - An Analytical algorithm of component-Based Heterogeneous Software Architectural Styles performance prediction
Golnaz Aghaee Ghazvini Sima Emadi

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107 - Simulation of Landuse Changes and Urban Dynamics using CA-Markov Hybrid Model Case Study: Maragheh City
Hoshang sarvar

In 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 More

In 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

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108 - Predicting land use changes with emphasis on residential lands using CA-Markov model Case study (Bojnourd plain catchment)
ahmad hoseinzadeh Abdolreza Kashki reza Javidi Sabaghian Mukhtar Karami

Understanding temporal and spatial changes in land use is essential for decision makers and community planners. Land use requires knowledge of the current trend and forecasting future developments in land use and land cover. In this study, using Landsat 7, 8 satellite i More

Understanding temporal and spatial changes in land use is essential for decision makers and community planners. Land use requires knowledge of the current trend and forecasting future developments in land use and land cover. In this study, using Landsat 7, 8 satellite images and Ca-Markov model in EDRISI TerrSet software, simulation and prediction of land use changes in Bojnourd catchment area in North Khorasan province has been performed. After making atmospheric and geometric corrections on the images of 2001 and 2019, a map predicting land use changes has been produced for 2040.The validation of the model is done through the kappa coefficient, the value of which is 0.92 for the land use map of 2001 and 0.95 for 2019. The results of the model prediction show that in the study area, residential lands with the increase of more than 5 thousand hectares during the study period have the most changes. Also, most of the changes have been made around the city of Bojnourd. Manuscript profile

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109 - 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 zakerhaghighi

Urban 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 More

Urban 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

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110 - بررسی تاثیر عوامل اقتصادی و غیر اقتصادی بر تقاضای انرژی در بخش کشاورزی ایران
مریم ضیاآبادی محمدرضا زارع مهرجردی

به دنبال رشد جمعیت، افزایش انتشار گازهای گلخانه‌ای و محدودیت منابع انرژی، تقاضای انرژی و عوامل موثر بر آن به موضوع مهمی تبدیل شده است. بررسی مصرف انرژی در بخش کشاورزی ایران نشان می‌دهد که طی سال‌های گذشته به منظور افزایش تولید، اشتغال و امنیت غذایی، مصرف انواع حامل‌های More

به دنبال رشد جمعیت، افزایش انتشار گازهای گلخانه‌ای و محدودیت منابع انرژی، تقاضای انرژی و عوامل موثر بر آن به موضوع مهمی تبدیل شده است. بررسی مصرف انرژی در بخش کشاورزی ایران نشان می‌دهد که طی سال‌های گذشته به منظور افزایش تولید، اشتغال و امنیت غذایی، مصرف انواع حامل‌های انرژی در این بخش افزایش یافته است. با توجه به اهمیت منابع انرژی و حفاظت محیط زیست، هدف این مطالعه بررسی تاثیر عوامل اقتصادی و غیر اقتصادی بر تقاضای انرژی دربخش کشاورزی ایران طی دوره 1396-1349 با استفاده از روش مارکوف سوئیچینگ- تصحیح خطای برداری می‌باشد. نتایج مطالعه حاکی از آن است که متغیر تولید بخش کشاورزی در هر دو رژیم مارکوف، دارای تاثیر مثبت و معنادار بر تقاضای انرژی در این بخش بوده است. متغیر تنوع فعالیت‌های کشاورزی تاثیر مثبت و معنادار بر مصرف انرژی در بخش کشاورزی داشته است. همچنین تاثیر متغیرهای سرمایه انسانی و آزادسازی تجارت بخش کشاورزی، بر مصرف انرژی در این بخش نیز مثبت و معنادار بوده است. بنابراین پیشنهاد می‌شود برای کاهش آلودگی محیط زیست و همچنین جلوگیری از کاهش تولید بخش کشاورزی، سیاست‌های مناسب برای مدیریت و بهینه‌سازی مصرف انرژی در این بخش اتخاذ شود. Manuscript profile

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111 - A two-sided Bernoulli-based CUSUM control chart with autocorrelated observations
S. M. T. Fatemi Ghomi F. Sogandi

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112 - Availability analysis of mechanical systems with condition-based maintenance using semi-Markov and evaluation of optimal condition monitoring interval
Girish Kumar Vipul Jain O. P. Gandhi

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113 - Accelerated decomposition techniques for large discounted Markov decision processes
Abdelhadi Larach S. Chafik C. Daoui

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114 - A time-shared machine repair problem with mixed spares under N-policy
Madhu Jain Chandra Shekhar Shalini Shukla

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115 - Markov modeling and reliability analysis of urea synthesis system of a fertilizer plant
Anil Kr. Aggarwal Sanjeev Kumar Vikram Singh Tarun Kr. Garg

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116 - A novel grey–fuzzy–Markov and pattern recognition model for industrial accident forecasting
Inyeneobong Ekoi Edem Sunday Ayoola Oke Kazeem Adekunle Adebiyi

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117 - Reliability analysis of repairable systems using system dynamics modeling and simulation
M. Srinivasa Rao V. N. A. Naikan

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118 - Mathematical modeling and fuzzy availability analysis for serial processes in the crystallization system of a sugar plant
Anil Kr. Aggarwal Sanjeev Kumar Vikram Singh

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119 - Performance evaluation of the croissant production line with reparable machines
Panagiotis H. Tsarouhas

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120 - Forecasting time and place of earthquakes using a Semi-Markov model (with case study in Tehran province)
Ramin Sadeghian

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121 - Bayesian change point estimation in Poisson-based control charts
Hassan Assareh Rassoul Noorossana Kerrie L Mengersen

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122 - Bi-product inventory planning in a three-echelon supply chain with backordering, Poisson demand, and limited warehouse space
Maryam Alimardani Fariborz Jolai Hamed Rafiei

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123 - Failure Probability of Damaged RC Frame under Fire Using Markov Chain.
MohammadJavad Goodarzi Hamidreza Tavakoli syyed milad hasheminejad alireza mohseni saravi majid moradi

10.30495/ijase.2023.1976830.1067

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124 - Management of the risk of cardiovascular disease with the help of mathematical models
samar shetaban mirmehdi esfehani sahar shetaban

Today, air pollution, smoking, use of fatty and ready-made foods, etc., have exacerbated heart disease. For this purpose, controlling the risk of such diseases can prevent or reduce their incidence. The present study aimed at using Markov decision processes (MDP) to est More

Today, air pollution, smoking, use of fatty and ready-made foods, etc., have exacerbated heart disease. For this purpose, controlling the risk of such diseases can prevent or reduce their incidence. The present study aimed at using Markov decision processes (MDP) to estimate the risk of cardiovascular disease. For this purpose, model inputs were first determined using a validated micro-simulation model for screening cardiovascular disease developed at Tehran University of Medical Sciences, Iran using genetic algorithm. The model input factors were then defined accordingly and using these inputs, three risk estimation models were identified. The results of these models support World Health Organization guidelines that provide medicine with high discount to patients with high expected Life Years. Finally, conflicts are usually observed in the risk models determining the likelihood of complications. Hence, to develop Markov Decision Processes methodology, policies should be adopted that work well despite the difference between the risk model and the actual risk. Manuscript profile

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125 - Mutual volatility of stock price index, gold and exchange rate: MSVAR approach
hamid hooshmandi

10.30495/ecomag.2024.1997614.1078

The main goal of the current research was to investigate the mutual effects of the stock exchange and two gold and foreign exchange markets using time series 2009(4) - 2022(11). The implementation of Lee-Strazicich unit root test indicates the occurrence of two structur More

The main goal of the current research was to investigate the mutual effects of the stock exchange and two gold and foreign exchange markets using time series 2009(4) - 2022(11). The implementation of Lee-Strazicich unit root test indicates the occurrence of two structural failures in the stock exchange and gold and foreign exchange markets in the decade of 2010. The optimal model, MSIAH-VAR(2), was selected. The findings of the research showed that the behavior of the total stock price index in Tehran Stock Exchange can be evaluated in two regimes (high volatility and low volatility). The results of the regime transition probability matrix indicated the stability and permanence of the low volatility regime and the weak possibility of transition between regimes. Therefore, when explanatory discussions enter the Tehran stock market, there is a possibility that these fluctuations or turbulences (in the form of a regime) will last a long time.The findings of the first model showed that there was a one-way shock transfer from the gold market to the Tehran Stock Exchange during the investigated period. According to the results of the second model, there is a one-way shock transfer from the stock exchange to the currency market. It can be concluded that in the Iranian economy, gold is of special importance in the portfolio of investors. In addition, shares, like currency, are an investment opportunity in the portfolio of Iranian investors. Manuscript profile

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126 - Islamic financing and mobilizing banking resources in Iran
seyyed ali paytakhti oskooe Arash Negahbani Nader Mehregan Mohammadreza Nahidi Amirkhiz

One of the most important functions of the Islamic financial system is to facilitate financial flow and divert financial resources for productive investment projects. This system gives banks the opportunity to move economic resources more quickly and accurately, relying More

One of the most important functions of the Islamic financial system is to facilitate financial flow and divert financial resources for productive investment projects. This system gives banks the opportunity to move economic resources more quickly and accurately, relying on monetary and financial resources, and the existence of Islamic financial instruments increases the productivity and optimal mobilization of banks' resources. In the present study, using Markov switching econometric technique the effect of Islamic financing (through rent sukuk and Murabaha bonds) on mobilizing banking resources in Iran has been investigated during the period 2012:4 to 2021:2 (based on quarterly data). The findings show that sukuk bonds in both regimes have a positive effect on bank deposits. In other words, the expansion of the sukuk has led to growth bank deposits. Therfore, we must look for ways to attract foreign and domestic investment in order to issue different types of sukuk. The use of these assets increases the resources of the banks. Manuscript profile

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127 - Presenting Comprehensive Algorithm for Long Term Scheduling of Preventive Maintenance in the Electric Transmission Networks
Niki Moslemi Mostafa Kazami Seyyed Mostafa Abedi Hadi Khatibzadeh Mohamad Jafarian Saeed Salimi

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128 - Persian Speech Recognition Through the Combination of ANN/HMM
Ladan Khosravani pour Ali Farrokhi

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129 - A Survey of Fractal Market Hypothesis with the Markov Regime change model in the Tehran Stock Exchange
یعقوب محمودی فریدون رهنمای رودپشتی شادی شاهوردیانی حمیدرضا کردلویی مهدی معدنچی زاج

The aim of this study is to test the Fractal Market Hypothesis with the Markov regime change model in the Tehran Stock Exchange.One of the concepts in the efficient market is whether the financial time series has long-term memory and fractal properties or not. Given the More

The aim of this study is to test the Fractal Market Hypothesis with the Markov regime change model in the Tehran Stock Exchange.One of the concepts in the efficient market is whether the financial time series has long-term memory and fractal properties or not. Given the characteristics of the capital market, which is always faced with random shocks and leads to fluctuations in this market, it is necessary to examine the fractal characteristics of the market.In this paper, the amount of long-term memory and stability of financial time series resulting from the total stock market index for the period 2009-2019 were examined. For this purpose, first, the existence of long-term memory was examined, and then the fractal nature of the market was examined using the Harst view index. The results indicate the existence of long-term memory in this variable. In this case, with one differentiation, it becomes more differentiated, so the stock price index series in Iran has long-term memory and the effects of each shock on this variable due to its long-term memory remain for long periods. The results also showed that the overall stock market index is fractal. Manuscript profile

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130 - The Role of Inflation Uncertainty onGas and Oil Consumption
Reza Ghaderi Moghadam Bijan Baseri Nemat Falihi Gholamreza Abbasi

10.30495/fed.2022.694713

The effects of inflation uncertainty and economic growth on oil and gas consumption in the Iranian economy are investigated. Using the family of GARCH models and annual data of inflation and economic growth during the period 1399-1360, the uncertainty behavior of inflat More

The effects of inflation uncertainty and economic growth on oil and gas consumption in the Iranian economy are investigated. Using the family of GARCH models and annual data of inflation and economic growth during the period 1399-1360, the uncertainty behavior of inflation and economic growth has been estimated. The cofficient show that the uncertainty of inflation and economic growth has significant effects on level of gas and oil Consumption.In addition, thereaction functions based on the Markov-switching approach, determinds that the shock of inflation and economic growth uncertainty has a positive effects on gas and oil consumption at the beginning of the period and has a negative effect after 4 periods. In the medium term, it has a negative effect on oil and gas consumption, which can not be in line with the sustainability of oil and gas consumption, in the long run, such conditions has no effect on oil and gas consumption and tends to zero after 20 periods. Manuscript profile

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131 - The management of optimal loan portfolio in banking sector: the case study of the Bank–e Saman
Mohsen Mehrara Soghra Sadeghian

This study aims to examine the optimal loan portfolio policy for Bank-e Saman, using the Markovitz modern portfolio model (2591). Generally, in Iran the Banks are allowed to offer loans to four economic sectors including services, manufacturing and mining, construction More

This study aims to examine the optimal loan portfolio policy for Bank-e Saman, using the Markovitz modern portfolio model (2591). Generally, in Iran the Banks are allowed to offer loans to four economic sectors including services, manufacturing and mining, construction and agriculture. Loans offered to production sectors are treated the most risky venture for the banking sectors. However, the results of this study indicate that the Bank-e Saman has pursued a desired diversification policy to maintain its optimal loan portfolio as advocated in Markovitz model. In its optimal loan portfolio policy, service sector has enjoyed the lion's share of 59 percent of bank's total loans portfolio, followed by manufacturing and mines, housing and construction, and agriculture respectively. The distribution of loan portfolio by economic sectors over the period of 2832 to 2839 (corresponding to 1001 to 1005) is proved to be inclined towards the optimal pattern. Yet, due to certain restriction inherited in Markovtz model, some of discrepancies or deviations in optimal loan performance can not be explained. Thus in order to be able to address such shortcomings, the model requires to include some factors such as the real need of credit market, based on the accommodation principle, into model. Besides some factors such as formal and informal regulations have a strong bearing on bank loan portfolios which should be taken into account as well. Manuscript profile

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132 - Nonlinear Effects of Financial Integration and Inflation on Labor Productivity in Selected Developing Countries: The Markov Switching Approach
Laleh Tabaghchi Akbari Mahmoud Babazadeh Ghasem Sameei Tahereh TaherehAkhundzadehYousefi

10.30495/fed.2022.697614

AbstractOne of the most tangible and effective areas of productivity, which the process of transformation at it, can have a significant impact on this very important indicator, is process of financial integration. Financial integration by integrating financial economies More

AbstractOne of the most tangible and effective areas of productivity, which the process of transformation at it, can have a significant impact on this very important indicator, is process of financial integration. Financial integration by integrating financial economies and relying more on market system and liberalization in its various dimensions can provide the basis for improving the productivity components. On the other hand, examining the impact of inflation on changes in growth rate of labor productivity is subject, which much attention in recent decades. Undoubtedly determination these effects can be helpful in adopting productivity policies. In this study, we investigate the nonlinear effects of financial integration and inflation on labor productivity in 15 selected developing countries at 2006 to 2019 with using of Markov Switching econometric technique. The results indicate that financial integration in both regimes, has a positive effect on labor productivity, but the intensity of this index impact is not very significant. There is also a Significant negative relationship about the effects of inflation on both regimes. Regarding the control variables, the business environment in first regime, has a negative effect and in second regime, it has a positive effect on labor productivity. Regarding the Institutional Factors Index, in the first regime has a positive relationship and in second regime has a negative relationship. Therefore, the need for new reform in these two areas is essential. So, it is necessary to make sustainable and cohesive planning to improve and development of financial integration indicators and also, control inflation in these societies, until  from  this way, to provide the grounds for promotion of labor productivity. Manuscript profile

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133 - Impact of Regional Rangeland Cover Degradation on Increasing Dusty Days in West of Iran
Hamid Nouri mohamad faramarzi seyed hadi sadeghi

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134 - The role of exchange rate fluctuations on private sector investment in housing in Tehran using the Markov switching regime model
Aliakbar Mehrabian yazdan gudarzi farahani

The purpose of this article was to investigate the role of exchange rate fluctuations on private sector investment in housing in Tehran. For this purpose, statistical data for the period 1970-2020 based on the frequency of annual data and the Markov switching regime app More

The purpose of this article was to investigate the role of exchange rate fluctuations on private sector investment in housing in Tehran. For this purpose, statistical data for the period 1970-2020 based on the frequency of annual data and the Markov switching regime approach have been used. In general, the developments in the housing sector play an essential role in intensifying the fluctuations of prosperity and stagnation of economic activities. Fluctuations in the return on other assets, such as currency, will affect demand for housing. When a monetary shock occurs, it changes the opportunity cost of maintaining durable goods, including housing, by changing interest rates, and this shock is due in part to the demand for housing resulting from the demand for services. The result of this property affects the housing. The results of this study showed that the exchange rate in the two currency regimes of high and low fluctuations has affected the investment of the private sector in housing in Tehran. The results also showed that the stability of the regime with high fluctuations in exchange rate volatility is greater than the stability of the regime with low fluctuations in exchange rate volatility. Manuscript profile

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135 - Reliability Assessment of Power Generation Systems in Presence of Wind Farms Using Fuzzy Logic Method
Shohreh Monshizadeh Mahmoud Reza Haghifam Ali Akhavein

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136 - Application of Generalized Geometric Bravoni Motion Model by Markov Switching Regime Process in Stock Price Simulation: System Dynamics Approach
Nahid Malekiniya Hosein Asgari Alouj zaher sepehrian

Objective: In this study, the changes of the stock price of Iran Khodro Company listed in Tehran Stock Exchange (TSE) has been studied on the issue of prediction modeling during of 9/13/1387 to 13/12/1396 based on Geometric Brownian Motion (GBM) model generalized by the More

Objective: In this study, the changes of the stock price of Iran Khodro Company listed in Tehran Stock Exchange (TSE) has been studied on the issue of prediction modeling during of 9/13/1387 to 13/12/1396 based on Geometric Brownian Motion (GBM) model generalized by the Markov switching regime (MSR).Methods: The research model was designed by system dynamics (SD) approach and Vensim DSS software in the causal- loop diagrams (CLD) firstly and then after specifying the flow-state variables, mono-loop and two-loop stock–flow diagrams (SFDs) was designed and daily final stock price was simulated. Two-parameter of noise seed and time step were identified and applied as sensitivity analysis parameters.Results: The simulation error was estimated for the random variations of the noise seed and the time step configured by default user parameters up to 22/74 and 30/35 percent, respectively. Both parameters were calibirated due to higher simulation error than acceptable error of 15 percent. Trial - error and field observation methods was performed in order to appropriate estimation of the calibration parameters range.The post-calibration accuracy of simulation per noise seed parameter increased from 77/26 to 91/5 percent and per time step from 69/65 to 96/37 percent.Conclusion: Findings indicate that the error roots have reached to the ideal mode by optimizing of the calibration parameters as covariance inequality error approached to one unit and base inequality error and variance inequality error approached to zero and indicate functionality accuracy of the GBM generalized by the MSR in stock price simulation. Manuscript profile

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137 - Design of Credit Risk Assessment Model by Predicting Credit Rating Transfer Using Markov Chain Process
Farid Heidarifar Farhad Hanifi gholamreza zomorodian

In 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 More

In 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

138 - The Effect of Exchange Rate Fluctuations on the Car Stock Index under Sanction Using Markove Switching Approach
Saman Houshmandi Seyed Shamsuddin Hosseyni Abbas Memarnejad Farhad Ghaffari

The present study tries to investigate the impact of the exchange rate fluctuations on the car stock index in Tehran Stock Exchange using the monthly data of the period of 1387:10-1398:12 and using the nonlinear Markov switching approach. For this purpose, among the var More

The present study tries to investigate the impact of the exchange rate fluctuations on the car stock index in Tehran Stock Exchange using the monthly data of the period of 1387:10-1398:12 and using the nonlinear Markov switching approach. For this purpose, among the various modes of Markov switching model, MSIAH(3) -VAR(2) has been selected. The empirical findings of the study show that only in a regime with high fluctuations, the exchange rate is the causal relationship of the car stock index and the increase in the exchange rate has increased the car stock index while the car stock index has no impact on the exchange rate. In addition, the results indicate that the sustainability of the car stock index in the regime with the very low fluctuations (first regime) was more than that of the regime with the low fluctuations (second regime) and that of the regime with the high fluctuations (third regime). Manuscript profile

Open Access Article

139 - Nonlinear Exchange Rate Analysis in the Iranian Economy
Mohammad abbasifard Seyed Abdolhamid Sabet Masoud Salehi Rezveh abdolkarim hosseinpour

Exchange rate pass-through (ERPT) means the impact of exchange rate fluctuations on domestic prices. The study of the relation between the exchange rate and the general level of domestic prices, known in the international financial literature as the exchange rate analys More

Exchange rate pass-through (ERPT) means the impact of exchange rate fluctuations on domestic prices. The study of the relation between the exchange rate and the general level of domestic prices, known in the international financial literature as the exchange rate analysis, has been one of the most important and fundamental topics in the economic literature. This study investigates the nonlinear exchange rate pass-through in the Iranian economy in the period 1984 to 2019 using the Markov switching method. The results show that in the period under review, for a one percent increase in the exchange rate, the inflation rate increases by 74 percent. In other words, transfer to prices is not complete and exchange rate transition in the Iranian economy is incomplete. The imperfection of the exchange rate passage is due to the fact that the price of imported goods is probably not only a function of the exchange rate, but also other factors have contributed to the fluctuation of these prices. Manuscript profile

Open Access Article

140 - Assessing the relationship between financial distress and stock returns using the Monte Carlo Markov chain
Monireh Dizaji

Monte 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 More

Monte 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

141 - Markov switching regime model in order to assess asset pricing and uncertainty in the stock market
Maryam Eydizadeh Hasan Ghodrati Ghazaani Aliakbar Farzinfar Hossein Panahian

The current research has been carried out with the aim of designing the Markov switching regime model in order to evaluate the asset pricing and uncertainty in the stock market in Iran's stock market. In order to estimate the Markov model by systematic elimination metho More

The current research has been carried out with the aim of designing the Markov switching regime model in order to evaluate the asset pricing and uncertainty in the stock market in Iran's stock market. In order to estimate the Markov model by systematic elimination method, 130 companies were selected and based on their performance, 1400 were divided into two categories, the top 50 companies and the lowest companies, and based on random processes to determine Markov regimes, investment portfolios were formed and based on the estimation of the Markov regime were estimated. The regression estimation of the relationship between efficiency and effective factors in the companies under investigation, regardless of the categories, showed that there was an inverse relationship between risk, normal and Laplace uncertainty degrees with efficiency, and the only determining factors were market risk and asset efficiency. , return on capital, profit volatility, cash flows, company value, asset liquidity, growth opportunities, asset turnover and company size have a significant relationship with stock returns. Among top companies, lower additional returns are usually associated with lower risk fluctuations and higher degree of uncertainty, and higher share risk spending is associated with higher risk fluctuations and lower degree of uncertainty. Manuscript profile

Open Access Article

142 - 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 Sahabi

In 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 More

In 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

143 - A Markov regime-switching model for crude-oil market fluctuations
mohammadreza Rostami maryam naghavipour maryam Moghaddasbayat

According 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 More

According 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

144 - 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 Nademi

Predictability 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 More

Predictability 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

145 - Iran Stock Market Prediction Based on Bayesian Networks and Hidden Markov Models
Zohreh Alamatian Majid Vafaei Jahan

Stock market behavior is one of the most complex mechanisms, considered by researchers. Financial markets are influenced by the external and internal factors. External factors such as political and social factors are not measurable, so prediction the trend of stock mark More

Stock market behavior is one of the most complex mechanisms, considered by researchers. Financial markets are influenced by the external and internal factors. External factors such as political and social factors are not measurable, so prediction the trend of stock markets is focused on internal factors. This study suggests a hybrid approach based on Bayesian Networks and Hidden Markov Models to predict trend of stock market. The used variables are 6 index of Tehran Stock Exchange, which have the most correlation coefficient with target stock, and 22 technical indicators. Bayesian networks are utilized to find the relationships between variables, and the effect of each variable in prediction considered from conditional probability tables. Hidden Markov Model is designed for sets of extract from Bayesian networks. The proposed model tested on four company’s stock names Mobarakeh Steel, Iran Khodro, Mellat Bank and Iran drug. The average accuracy of the proposed system is 83.26 %. The experimental results show that the suggested procedure has higher performance for prediction of stock markets in comparison with other previous methods. Manuscript profile

Open Access Article

146 - To Forecat the Recession and Prosperity in the Tehran Stock Exchange using Models of MS and NSGA-ANN
farzaneh abdollahian Mohammad Ebrahim Mohammad Pourzarandi Mohammad Hasheminejad Mehrzad Minouei

The stock exchange is one of the financial instruments of countries around the world. The recession in this market can have important effects, for example reducing liquidity, reducing the profitability of companies admitted to the stock exchange, and reducing economic g More

The stock exchange is one of the financial instruments of countries around the world. The recession in this market can have important effects, for example reducing liquidity, reducing the profitability of companies admitted to the stock exchange, and reducing economic growth. In this paper, we are looking for extraction and prediction of time cycles in the stock market. Initially, using the total stock index and the MSI (3) AR (2) model, three cycles of recession, medium prosperity and high prosperity are extracted in the stock market. Then the most important predictor variables are determined by using the integration of the NSGA (II) algorithm and the three types of neural network models and predicted the market situation for the next three months. Finally, the performance of three types of multilayer perceptron neural network, radial basis and probable network were compared in terms of feature selection and prediction of future market situation. The results indicate that all three models  have  acceptable  error  rates,  accuracy,  and Kappa  coefficients, and the probable network model has lower error rate, more accuracy and kappa coefficient than other models. Manuscript profile

Open Access Article

147 - Evaluation the effect of stochastic fluctuations on operational risk of hedging European options: Application of Markov Switching and Black Scholes Standard
Mahmoud Zarrini seyed parviz jalili kamju Razyeh Goodarzi

Operational risk is not general definition and it has a unique definition for each company, which depends on the industry and the market of the company. The purpose of this research is to evaluate the effect of stochastic fluctuations on operational risk hedging Europea More

Operational risk is not general definition and it has a unique definition for each company, which depends on the industry and the market of the company. The purpose of this research is to evaluate the effect of stochastic fluctuations on operational risk hedging European options on the S & P500 index. So this research will compare the operational risk level in the Markov Switching and Black Scholes models using the Var. The implicit volatility values for the three confidence levels of 90, 95 and 99% for different values of call options K, different maturity T, and different interest rate r were calculated for both models using S & P500 index call options information. The results of this study showed that due to higher gamma and random variation of operational risk, the coverage of transaction options in the Markov Switching Model compared to the Black Scholes Standard model was higher by using the criterion of value-at-risk op Var's coverage is at 90, 95, and 99 levels. The results show that OP VaR is inversely proportional to  ,    It also reduced doubling of the OP Variant's maturity over the agreed price. Finally, the results show that the interest rate has an asymmetric effect on OP VaR. As is clear from the figure, for K <S, the OP VaR has been lowered by rising interest rates, and for K> S interest rates have reduced OP VaR . Manuscript profile

Open Access Article

148 - Markov Chain Analogue Year Daily Rainfall Model and Pricing of Rainfall Derivatives
Tesfahun Berhane Nurilign Shibabaw Tesfaye Kebede

Manuscript profile

Open Access Article

149 - The Lindley-Lindley Distribution: Characterizations, Copula, Properties, Bayesian and Non-Bayesian Estimation
Christophe Chesneau Haitham Yousof G. Hamedani Mohamed Ibrahim

10.30495/ijm2c.2021.681361

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Open Access Article

150 - DISCRETE-TIME GI/D-MSP/1/K QUEUE WITH N THRESHOLD POLICY
Veena Goswami P. Vijaya Laxmi

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Open Access Article

151 - ANALYSIS OF FINITE BUFFER RENEWAL INPUT QUEUE WITH BALKING AND MARKOVIAN SERVICE PROCESS
Vijaya Laxmi Pikkala Jyothsna Kanithi

Manuscript profile

Open Access Article

152 - AN APPLICATION OF TRAJECTORIES AMBIGUITY IN TWO-STATE MARKOV CHAIN
M. Khodabin

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Open Access Article

153 - Optimal hedging of quantitative risk based on Markov regime change in coin futures contract
Sayyed Mohammad Reza Davoodi Marzieh Karami Chamgordani Sayyed AmirReza Hashemi

10.30495/afi.2023.1966058.1152

Objective: One of the key roles of futures markets is to provide risk hedging tools. The optimal strategy for risk hedging is determined by estimating the risk hedging ratio. Calculating the risk hedging ratio and the effectiveness of hedging explicitly depend on the re More

Objective: One of the key roles of futures markets is to provide risk hedging tools. The optimal strategy for risk hedging is determined by estimating the risk hedging ratio. Calculating the risk hedging ratio and the effectiveness of hedging explicitly depend on the relationship between futures prices and spot prices. Therefore, the aim of this study is to estimate the optimal risk hedging ratio in various timeframes under low and high volatility conditions using a Markov regime-switching multivariate regression model.Methodology: The slope obtained from the Markov regime-switching multivariate regression, representing the optimal risk hedging ratio, is chosen, which is dependent on the choice of timeframes and two cases for the multivariate regression model are adopted according to the level of volatility considered.Findings: The research results on 5 futures contracts in the period from 2014 to 2018 indicate that in three markets, normal (composite), low volatility, and high volatility, risk hedging has been able to reduce risk by at least 20%. In the high volatility market, the optimal risk hedging ratio has reduced volatility by at least 23% in all timeframes (with the mean square error criterion), and the 0/95 timeframe performs the best in terms of the highest reduction in volatility and the lowest risk hedging ratio. In the low volatility market, the optimal risk hedging ratio has reduced volatility by at least 58% in all timeframes, and the 0/05 timeframe performs the best in terms of the highest reduction in volatility and the lowest risk hedging ratio. In the composite market, the optimal risk hedging ratio has also reduced volatility by 21%.Originality / Value: The results of this study not only contribute to the literature on risk hedging but also assist all stakeholders and users in evaluating the level of attention to the risk hedging topic. Manuscript profile

Open Access Article

154 - The Improved Semi-Parametric Markov Switching Models for Predicting Stocks Prices
hossien naderi Mehrdad Ghanbari Babak Jamshidi Navid Arash Nademi

The modeling of strategies for buying and selling in Stock Market Investment have been the object of numerous advances and uses in economic studies, both theoretically and empirically. One of the popular models in economic studies is applying the Semi-parametric Markov More

The modeling of strategies for buying and selling in Stock Market Investment have been the object of numerous advances and uses in economic studies, both theoretically and empirically. One of the popular models in economic studies is applying the Semi-parametric Markov Switching models for fore-casting the time series observations based on stock prices. The Semi-parametric Markov Switching models for these models are a class of popular methods that have been used extensively by researchers to increase the accu-racy of fitting processes. The main part of these models is based on kernel and core functions. Despite of existence of many kernel and core functions that are capable in applications for forecasting the stock prices, there is a widely use of Gaussian kernel and exponential core function in these mod-els. But there is a question if other types of kernel and core functions can be used in these models. This paper tries to introduce the other kernel and core functions can be offered for good fitting of the financial data. We first test three popular kernel and four core functions to find the best one and then offer the new strategy of buying and selling stocks by the best selection on these functions for real data. Manuscript profile

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