대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)

대한전기학회 (The Korean Institute of Electrical Engineers)
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비선형 모델링에 대한 새로운 뉴로-퍼지 네트워크 연구

A study on the novel Neuro-fuzzy network for nonlinear modeling

  • 김동원 (원광대학교 공과대학 제어계측공학과) ;
  • 박병준 (원광대학교 공과대학 제어계측공학과) ;
  • 오성권 (원광대학교 공과대학 제어계측공학과)
  • Kim, Dong-Won (School of Electrical and Electronic Engineering, Wonkwang Univ.) ;
  • Park, Byoung-Jun (School of Electrical and Electronic Engineering, Wonkwang Univ.) ;
  • Oh, Sung-Kwun (School of Electrical and Electronic Engineering, Wonkwang Univ.)
  • 발행 : 2000.11.25
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초록

The fuzzy inference system is a popular computing framework based on the concepts of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. The advantage of fuzzy approach over traditional ones lies on the fact that fuzzy system does not require a detail mathematical description of the system while modeling. As modeling method. the Group Method of Data Handling(GMDH) is introduced by A.G. Ivakhnenko GMDH is an analysis technique for identifying nonlinear relationships between system's inputs and output. We study a Novel Neuro-Fuzzy Network (NNFN) in this paper. NNFN is a network resulting from the combination of a fuzzy inference system and polynomial neural network(PNN) (7) which is advanced structure of GMDH. Simulation involve a series of synthetic as well as experimental data used across various neurofuzzy systems.

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