Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
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The Identification of Multi-Fuzzy Model by means of HCM and Genetic Algorithms

클러스터링 기법과 유전자 알고리즘에 의한 다중 퍼지 모델으 동정

  • Park, Byoun-Jun (School of Electrical and Electronic Engineering, Wonkwang Univ.) ;
  • Lee, Su-Gu (School of Electrical and Electronic Engineering, Wonkwang Univ.) ;
  • Oh, Sung-Kwun (School of Electrical and Electronic Engineering, Wonkwang Univ.) ;
  • Kim, Hyun-Ki (School of Electrical Engineering, Suwon Univ.)
  • 박병준 (원광대학교 전기전자공학부) ;
  • 이수구 (원광대학교 전기전자공학부) ;
  • 오성권 (원광대학교 전기전자공학부) ;
  • 김현기 (수원대학교 전기전자정보통신공학부)
  • Published : 2000.07.17
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Abstract

In this paper, we design a Multi-Fuzzy model by means of clustering method and genetic algorithms for a nonlinear system. In order to determine structure of the proposed Multi-Fuzzy model. HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy are identified by genetic algorithms. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy model and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

Keywords