List of Articles Intelligent Algorithm

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  1 - The Predication of Stock Price Using Firely Algorithm
  Ali Bayat Zeynab Bagheri
  In this study, the prediction of stock price of some manufactors listed in Tehran stock market and some others, using firefly algorithm has be done.In this study firstly, we used 16 variables for a period of 3 years (1388-1392) to educating the algorithm and after that More

  In this study, the prediction of stock price of some manufactors listed in Tehran stock market and some others, using firefly algorithm has be done.In this study firstly, we used 16 variables for a period of 3 years (1388-1392) to educating the algorithm and after that , we used educated algorithm to predict the stock price of manufactors with 12 variables. the relative fault was calculated for stock prices for before and after prediction. the average of This fault isless than %6 and the result is that the stock price prediction using fire fly algorithm is achievable and possible. Manuscript profile
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  2 - Financial Reporting Readability: A new Artificial Neural Network and Multi-Indicator Decision Making Approach
  Ali Asghar Khazaei Harivand Arash Naderian Majid  Ashrafi Ali  Khozin
  The desirability of the financial reporting can greatly help the users of finan-cial information in making investment decisions. The purpose of this re-search is to measure the readability of financial reporting using a multi-indicator decision-making model and the arti More

  The desirability of the financial reporting can greatly help the users of finan-cial information in making investment decisions. The purpose of this re-search is to measure the readability of financial reporting using a multi-indicator decision-making model and the artificial neural network method and the role of information presentation time in its improvement. In this research, various indicators have been used to measure the readability of financial reporting, and the quality of reporting is obtained through the rank-ing of companies by the stock exchange. In this research, the number of 149 companies admitted to the Tehran Stock Exchange in the period of 2010-2020 was examined, and to measure the financial readability through struc-tural equations and Stata software, and to test the hypothesis of the research, the regression model and Eviews econometrics software were used. In this study, we have tried to Use machine learning techniques and optimization tools as a way to derive adaptive-robust nonlinear models that can reduce the risk of model error as much as possible. The findings of the research show that the time of providing information has an impact on the readability of financial reporting. The obtained outputs from the estimation of the artificial neural networks and results obtained from estimation, using of this method with evaluation scales concerning random amount and comparing it with adjusted R, we found that there is meaningful relation between the associated variables and return. However, such network has the least error than other networks. The results show an overall improvement in forecasting using the neural network as compared to linear regression method. In other words, our proposed system displays an extremely higher profitability potential. The obtained result can be argued that the more the company's information is provided by the managers to the company's shareholders and investors on time and at the right time, the more readable and understandable the financial reports will be. Manuscript profile
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  3 - Agility Agents In Supply Chain of Educational Organizations Using Particle Swarm Optimization Algorithm
  Abbass Toloie Ashlaghi shahrzad tayaran Reza Radfar Alireza Pourebrahimi
  The increasing speed of technological change, on the one hand, and the changing nature of customer demand and the intensification of competition among organizations, on the other hand, have led organizations to seek to take on new competitive advantages to outperform co More

  The increasing speed of technological change, on the one hand, and the changing nature of customer demand and the intensification of competition among organizations, on the other hand, have led organizations to seek to take on new competitive advantages to outperform competitors and better meet customer needs. Achieving such goals comes in the context of a new concept called "organizational agility," but agility of the organization is influenced by its agents, which are the most influential factor in service companies. In this research, which the University of Science and Research has proposed as a case study, the employees are divided into three categories: Soft, Grievous, and Blind. These factors determine the three main elements of the agility of the supply chain organization: Agility drivers, agility abilities and agility capability. Also, using a particle swarm optimization algorithm, an intelligent model has been designed to measure the impact and impact of factors on each other. And after implementing the model in a case study at Time = 769, recovery is at best possible. Manuscript profile