A Study on Optimal Fuzzy Identification by means of Hybrid Identification Algorithm

  • Park, Byoung-Jun (Dept., of Control & Instrumentation Engineering Wonkwang University) ;
  • Park, Chun-Seong (Dept., of Control & Instrumentation Engineering Wonkwang University) ;
  • Oh, Sung-Kwun (Dept., of Control & Instrumentation Engineering Wonkwang University)
  • Published : 1998.10.01

Abstract

In order to optimize fuzzy model, we use the optimal algorithm with a hybrid type in the identification of premise parameters and standard least square method in the identification of consequence parameters of a fuzzy model. The hybrid optimal identification algorithm is carried out using a genetic algorithm and improved complex method. Also, the performance index with weighting factor is proposed to achieve a balance between the insults of performance for the training and testing data. Several numerical examples are used to evaluate the performance of the proposed model.

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