درخت حوزه‌های تخصصی

Purpose: The purpose of this research was to provide a model for predicting time series of financial information based on the Lyapunov representation of information using chaos theory.Method: This research is applied in its purpose, which is conducted using a quantitative approach. The research ranks as descriptive-causal accounting research based on actual information in companies' financial statements. The research method is the "post-event" type and was carried out using chaos theory and Saida's method based on the Lyapunov view.Findings: The findings showed that during the ADF test, the null hypothesis was rejected at a level of less than 5% type 1 error and 95% confidence, and it shows that the data is not static. During the substitution analysis test and its significance level, the behavior of the time series of the main financial information is significantly different compared to their substitutes. The obtained value was calculated to describe the production process of all data sets for μ = 2, ApEnMax equal to 0.65 and rMax equal to 0.32, and for μ = 3, ApEnMax equal to 0.6 and rMax equal to 0.44. The value of the Lyapunov profile in stability at a certain point is less than zero and in the limited cycle of stability is equal to zero and in chaos, it is greater than zero and smaller than ∞, and in noise it is equal to ∞.Conclusion: The results show that higher returns, encourage investors to invest and increase the flow of capital. It is believed that companies' stock returns are a function of systematic risk, and systematic risk represents the changes in the return rate of a share compared to the changes in the return rate of the entire stock market.

Performance evaluation, as a tool to know the degree of success of organizations in achieving predetermined goals and a factor in managers' decisions, has been one of the constant needs of organizations. The purpose of this research is to identify performance evaluation indicators and explain the appropriate performance evaluation model in Macro government organizations such as Jam Petrochemical Company. This research is based on the purpose of applied research and also based on the research method with a mixed or combined approach with a sequential exploratory strategy. The required data were collected through qualitative research (interview) and quantitative research (questionnaire). In the quantitative part, the current research can be considered as a non-experimental (descriptive) type of research and a survey type. To analyze the data of the questionnaire, this research has been done in four phases, the first phase is to identify and rank the strengths and weaknesses of Jam Petrochemical Company, and the second phase is to use a Delphi test to identify indicators that are effective in evaluating the performance of Jam Petrochemical Company. The third phase is exploratory factor analysis and determining Dimensions of performance evaluation in Jam Petrochemical Company and finally the fourth phase of structural equations and path analysis. The results of the research showed that considering that the T-statistic for all variables is more significant than 1.96 and also considering the positiveness of the path coefficients, the variables (scientific observation, technology and technology, financial management, managers' responsibility, infrastructure management, management and leadership and human resources) are among the factors that make up the performance evaluation system in Jam Petrochemical Company.

Environmental pollution and rapid depletion are among the chief concerns about fossil fuels such as oil, gas, and coal. Renewable energy sources do not suffer from such limitations and are considered the best choice to replace fossil fuels. The present study develops a mathematical model for optimal allocation of regional renewable energy to meet a country-wide demand and its other essential aspects. The ultimate purpose is to minimize the total cost by planning, including power plant construction and maintenance costs and transmission costs. Minimum-cost flow equations are embedded in the model to determine how regions can supply energy to other regions or rely on them to fulfill annual demand. In order to verify the applicability of the model, it is applied to a real-world case study of Iran to determine the optimal renewable energy generation-transmission decisions for the next decade. Results indicate that the hydroelectric and solar power plants should generate the majority of the generated renewable electricity within the country, according to the optimal solution. Moreover, regarding the significant population growth and waste generation in the country’s large cities, biomass power plants can have the opportunity to satisfy a remarkable portion of electricity demand.