대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)

대한전기학회 (The Korean Institute of Electrical Engineers)
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퍼지추론규칙과 PNN 구조를 융합한 FPNN 알고리즘

The FPNN Algorithm combined with fuzzy inference rules and PNN structure

  • 박호성 (원광대학교 전기전자공학부) ;
  • 박병준 (원광대학교 전기전자공학부) ;
  • 안태천 (원광대학교 전기전자공학부) ;
  • 오성권 (원광대학교 전기전자공학부)
  • Park, Ho-Sung (Division of Electrical & Electronic Engineering, Wonkwang Univ.,) ;
  • Park, Byoung-Jun (Division of Electrical & Electronic Engineering, Wonkwang Univ.,) ;
  • Ahn, Tae-Chon (Division of Electrical & Electronic Engineering, Wonkwang Univ.,) ;
  • Oh, Sung-Kwun (Division of Electrical & Electronic Engineering, Wonkwang Univ.,)
  • 발행 : 1999.07.19
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초록

In this paper, the FPNN(Fuzzy Polynomial Neural Networks) algorithm with multi-layer fuzzy inference structure is proposed for the model identification of a complex nonlinear system. The FPNN structure is generated from the mutual combination of PNN (Polynomial Neural Network) structure and fuzzy inference method. The PNN extended from the GMDH(Group Method of Data Handling) uses several types of polynomials such as linear, quadratic and modifled quadratic besides the biquadratic polynomial used in the GMDH. In the fuzzy inference method, simplified and regression polynomial inference method which is based on the consequence of fuzzy rule expressed with a polynomial such as linear, quadratic and modified quadratic equation are used Each node of the FPNN is defined as a fuzzy rule and its structure is a kind of fuzzy-neural networks. Gas furnace data used to evaluate the performance of our proposed model.

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