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EXTENDED ABSTRACTINTRODUCTION Human Development Index is a composite one to measure three criteria of longevity, access to knowledge and appropriate level of welfare. Since 2011, education, the combination of mean study years for adults (25 years of age and elder) and expected years of studying, life expectancy and income per capita have been considered as components of Human Development Index. Human Development Index is in fact the geometrical mean of these three indexes. This index is annually calculated for countries by the United Nations but not for their states, provinces, cities and regions. Therefore, researchers themselves must calculate this index for provinces for certain purposes. METHODOLOGYLack of such statistics is also a statistic deficit in Iran that has made regional and provincial researches limited and inaccurate. To remove this deficit in this research Khouzestan Human Development Indexes in the years 1996, 2006, 2011 and 2016 have been calculated using the latest formula. It needs to be mentioned that the simulation of Human Development Index is difficult and time consuming. Not paying attention to details can deviate the index. So in order to ensure the precision of calculations, the Human Development of the country has also been calculated and compared with the same index calculated by the United Nations for Iran in order to ensure the authenticity of Human Development Index in Khouzestan. The applied method was a simultaneous behavioral pattern which considers the changes in Human Development Index through components of the United Nations Human Development Index and also simultaneously predicts and includes it in Human Development Index. The estimation method is based on Stock and Watson (1993) Dynamic least squared method that is helpful for predicting variables. FINDINGSAccording to results, Khouzestan Human Development Index for the period 1990-2019 can be simulated. The related results are presented in table 1. Table 1. Simulation of Khuzestan Human Development IndexFor further investigation of the results of simulation with real data, the results of calculating simulation assessment criteria have been shown in table 2. The results verify the validity of simulation. Table 2. prediction error criteriaAs table 10 shows, Khouzestan Human Development Index had a slow rising trend up until 2005 but from 2006, there seems to be a jump or structural failure in Human Development Index. However, during 2016-2018 the trend reached a plateau and it seems to have reached its stabilized level. Also, based on this simulation Khouzestsan Human Development Index was in an average level up until 2008 but since 2009 it has reached its high. CONCLUSIONTo assess this hypothesis, in this research using the new formula Khouzestan Human Development Indexes for the years 1996, 2006, 2011 and 2016 were calculated. The results showed that the indexes of life expectancy and education in Khouzestan were in a worse situation than that of the country but the index of income (taking oil into account) was more than that of the country. The calculation of Khouzestan Human Development Index without oil showed a worse situation than that of the country.Based on results, Kouzestan Human Development Index reached from an average level in 1996 to a high level during 2006 to 2016. This is an acceptable growth. Also, Khouzestan Human Development Index without oil is lower than that of the national index and this represents the worse status of the province compared to the country.The results of simulating Human Development Index show that up until 1389, there was a slight rising trend but from this year on there has been a jump or failure. Moreover, Khouzestan Human Development Index was in an average level up to 1385 but it has reached a high one since 2010.

The purpose of this research is to provide a growth model of fixed assets based on the financial criteria of companies admitted to the Tehran Stock Exchange. The current research is applied in terms of objective classification and descriptive-correlation in terms of method. The research method is de-ductive-inductive. The statistical population of the current research is all the companies admitted to the Tehran Stock Exchange in the period from 2012-2021 and the financial information of 101 companies are use. Research hypotheses were tested using artificial intelligence algorithm. In this research, investment in fixed assets has been consider as a dependent variable, and financial criteria has been considered as primary independent variables. The results of research hypotheses testing using the methods of linear and non-linear algorithms of artificial intelligence PINSVR and KPLSR in predicting fixed asset investors of companies and by calculating the three errors criteria MAE, MSE and SMAPE in annual fixed assets. The asset forecasting in the next year of companies showed that the error difference between linear models and non-linear models is not so great that it can be claim that linear models are ineffective in predicting asset growth so that artificial intelligence algorithms are capable of predicting investment in company assets.

The price of Crude Oil is Exposed to Various Factors That Cause Random, Sudden and Chaotic Price Fluctuations. Accurate Forecasting of Oil Prices Has a Central Impact on The Macro Economy. The aim of This Study is to Predict the Fluctuations of OPEC Crude Oil in The  long-term Using Chaos Theory and GMDH-GA Algorithm. First, the Daily Oil Price Time Series is Decomposed by Wavelet Transformation. Then, Chaos is Tested Using Embedding Dimension, Lyapunov Power and GA tests. Finally, Time Series Noises are Reduced by Reconstructing the Wavelet Phase Space. Three Nonlinear Models, GMDH-GA model, GMDH-GA Wavelet Model, and GMDH-GA Extended Model, Were Used to Forecast Time Series. Although the Results Showed that All three Models are Favorable in Terms of Root Mean Square Error (RMSE) and Correlation Coefficient, But the Developed GMDH-GA  Neural Network Model with low RMSE and High Correlation Coefficient is the Most Effective in Predicting the Daily Price of OPEC Crude Oil. has it.

Purpose: The present study aimed to improve the quality of delivering government services by identifying the main components of the personalization of the m-government in Iran.Method: Qualitative approach and exploratory research is applied. Data is gathered by targeted sampling and semi-structured interviews. Thematic analysis technique was used to analyze the interviews.Findings: The research findings indicate that the personalization of mobile government in Iran includes five main themes and 16 sub-themes including social factors (e-services, e-participation), e-factors (productivity, policy making), managerial factors (accountability, human capital, transparency), political factors (e-legislation, information technology infrastructure), cultural factors (e-support, e-learning).Conclusion: Experts emphasized on managerial factors like accountability and transparency of government activities. Also cultural factors are very important as digital literacy of society is very important in this regard. On the other hand regular review and update of current laws of ICT infrastructures and security policies should be considered as important by government. Also targeted filtering by personal information will make citizens more satisfied to receive updated information and related services based on their needs and preferences.