웨이브렛 변환과 유전 알고리듬을 이용한 퍼지 모델링

Fuzzy Modeling Using Wavelet Transform and Genetic Algorithm

  • 이승준 (연세대 공대 전기.컴퓨터공학과) ;
  • 주영훈 (군산대 공대 전자정보공학부) ;
  • 박진배 (연세대 공대 전기.컴퓨터공학과)
  • Lee, Seung-Jun (Dept. of Electrical & Computer Engineering, Yonsei Univ.) ;
  • Joo, Young-Hoon (School of Electronics & Information Engineering, Kunsan National Univ.) ;
  • Park, Jin-Bae (Dept. of Electrical & Computer Engineering, Yonsei Univ.)
  • 발행 : 2000.07.17

초록

This paper addresses the use of a nonlinear modeling procedure which construct a wavelet-based fuzzy model using genetic algorithm. A fuzzy inference system has the functional equivalence with a wavelet transform. Therefore, a wavelet-based fuzzy model using GA inherits the advantage of wavelet transform. Hereby, its performance is promoted. By help of the ability of GA to search the optimum globally, parameters of wavelet transform is determined closely to the optimal point. The feasibility of the proposed fuzzy model is proved by modelling a highly nonlinear function and comparing it with previous research.

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