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Identification of A Nonlinear System By Determining of Fuzzy Rules
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نویسنده
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Hamidi Hojjatollah ,Daraei Atefeh
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منبع
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Journal Of Information Systems And Telecommunication - 2016 - دوره : 4 - شماره : 4 - صفحه:215 -220
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چکیده
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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.
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کلیدواژه
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Data Mining ,Classification ,Heart Disease ,Diagnosis ,Prognosis ,Treatment
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آدرس
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K.N.Toosi University Of Technology, Department Of Industrial Engineering, ایران, K.N.Toosi University Of Technology, Department Of Industrial Engineering, ایران
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پست الکترونیکی
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adaraei@mail.kntu.ac.ir
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Authors
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