Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
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Implementation of Fuzzy Self-Organizing Networks Algorithm and Its Application to Nonlinear Systems

퍼지 자기구성 네트워크 알고리즘의 구현 및 비선형 시스템으로의 응용

  • Park, Byoung-Jun (Dept. of Control & Instrumentation Engineering, Wonkwang Univ.) ;
  • Kim, Dong-Won (Dept. of Control & Instrumentation Engineering, Wonkwang Univ.) ;
  • Lee, Dae-Keun (Dept. of Control & Instrumentation Engineering, Wonkwang Univ.) ;
  • Oh, Sung-Kwun (Dept. of Control & Instrumentation Engineering, Wonkwang Univ.)
  • 박병준 (원광대학교 제어계측공학과) ;
  • 김동원 (원광대학교 제어계측공학과) ;
  • 이대근 (원광대학교 제어계측공학과) ;
  • 오성권 (원광대학교 제어계측공학과)
  • Published : 2000.07.17
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Abstract

In this paper. we propose Fuzzy Self-Organizing Networks (FSON) using both Polynomial Neural Networks(PNN) and Fuzzy Neural Networks(FNN) for model identification of complex and nonlinear systems. The proposed FSON is generated from the mutually combined structure of both FNN and PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get the better output performance with superb predictive ability. In order to evaluate the performance of proposed models. we use the nonlinear data sets. The results show that the proposed FSON can produce the model with higher accuracy and more robustness than previous any other method.

Keywords