대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)

대한전기학회 (The Korean Institute of Electrical Engineers)
권호 표지

HCM 및 최적 알고리즘을 이용한 퍼지-뉴럴네트워크구조의 설계

Design of Fuzzy-Neural Networks Structure using HCM and Optimization Algorithm

  • 윤기찬 (원광대학교 전기전자공학부) ;
  • 박병준 (원광대학교 전기전자공학부) ;
  • 오성권 (원광대학교 전기전자공학부)
  • Yoon, Ki-Chang (Dept. of Electrical and Electronic Engineering, Wonkwang Univ.) ;
  • Park, Byoung-Jun (Dept. of Electrical and Electronic Engineering, Wonkwang Univ.) ;
  • Oh, Sung-Kwun (Dept. of Electrical and Electronic Engineering, Wonkwang Univ.)
  • 발행 : 1998.11.28
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초록

This paper presents an optimal identification method of nonlinear and complex system that is based on fuzzy-neural network(FNN). The FNN used simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM Algorithm to find initial parameters of membership function. And then to obtain optimal parameters, we use the genetic algorithm. Genetic algorithm is a random search algorithm which can find the global optimum without converging to local optimum. The parameters such as membership functions, learning rates and momentum coefficients are easily adjusted using the genetic algorithms. Also, the performance index with weighted value is introduced to achieve a meaningful balance between approximation and generalization abilities of the model. To evaluate the performance of the FNN, we use the time series data for 9as furnace and the sewage treatment process.

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