مرکز منطقه ای اطلاع رسانی علوم و فناوری Journal of Information Systems and Telecommunication (JIST) 2322-1437 4 16 2016 12 24 Identification of a Nonlinear System by Determining of Fuzzy Rules Identification of a Nonlinear System by Determining of Fuzzy Rules 1 10 10.7508/jist.2016.04.002 en hojatallah hamidi Departm K. N. Toosi University of Technology, Tehran, Iran Atefeh Daraei K. N.Toosi University of Technology 2017 1 14 In this article the hybrid optimization algorithm of differential evolution and particle swarm is introduced for designing the fuzzy rule base of a fuzzy controller. For a specific number of rules, a hybrid algorithm for optimizing all open parameters was used to reach maximum accuracy in training. The considered hybrid computational approach includes: opposition-based differential evolution algorithm and particle swarm optimization algorithm. To train a fuzzy system hich is employed for identification of a nonlinear system, the results show that the proposed hybrid algorithm approach demonstrates a better identification accuracy compared to other educational approaches in identification of the nonlinear system model. The example used in this article is the Mackey-Glass Chaotic System on which the proposed method is finally applied. http://jist.ir/ar/Article/Download/14995