Adaptation of Clustering Method to FNN for Performance Improvement

FNN 성능개선을 위한 클러스터링기법의 적용

  • 최재호 (원광대학교 제어계측공학과) ;
  • 박춘성 (원광대학교 제어계측공학과) ;
  • 오성권 (원광대학교 제어계측공학과) ;
  • 안태천 (원광대학교 제어계측공학과)
  • Published : 1997.10.01

Abstract

In this paper, we proposed effective modeling method to nonlinear complex system. Fuzzy Neural Network(FNN) was used as basic model. FNN was fused of Fuzzy Inference which has linguistic property and Neural Network which has learning ability and high tolerence level. This paper, we used FNN which was proposed by Yamakawa. The FNN used Simple Inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. This structure has better property than other structure at learning speed and convergence ability. But it has difficulty at definition of membership function. We used Hard c-Mean method to overcome this difficulty. To evaluate proposed method. We applied the proposed method to waste water treatment process. We obtained better performance than conventional model.

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