The Modeling of Exchange Rate Predict in Iran by Using Neural Network Based on Genetic Algorithms and Particle Swarm Algorithm
Subject Areas : Bi-quarterly Journal of development economics and planningali jamali 1 , saeed daie karimzadeh 2
1 - Department of management, Parand branch
2 - Associate Professor, Department of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
Keywords: Exchange Rate, artificial neural networks, genetic algorithms, Particle Swarm algorithm.,
Abstract :
In recent years the use of artificial intelligence techniques in the financial and investment markets instead of customary quantitative methods has been increasing and gives better performance towards classic methods usually. Artificial Neural Network (ANN), has weaknesses points despite its enormous benefits also. In this study, in order to overcome the weaknesses of the network consists of combining artificial intelligence methods with Evolutionary algorithms, means of artificial neural network combined with genetic algorithm (GA) and Particle Swarm algorithm (PSO) to model and daily predict of nominal exchange rates or the exchange rate dollar by Rial in Iran in the period 21.03.2013 to 22.12.2019 is used. This combined model with neural networks method as one artificial intelligence model according to the criteria of MSE , RMSE, MAE, U.Theil compared. The results of this research show the superiority of synthetic neural network model -Particle Swarm algorithm compare to other models of investigation.
