대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)

대한전기학회 (The Korean Institute of Electrical Engineers)
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수정된 GMDH 알고리즘 기반 다층 퍼지 추론 시스템에 관한 연구

A Study on Multi-layer Fuzzy Inference System based on a Modified GMDH Algorithm

  • 박병준 (원광대학교 전기전공학부) ;
  • 박춘성 (원광대학교 전기전공학부) ;
  • 오성권 (원광대학교 전기전공학부)
  • Park, Byoung-Jun (Division of Electrical and Electronic Engineering, Wonkwang Univ.) ;
  • Park, Chun-Seong (Division of Electrical and Electronic Engineering, Wonkwang Univ.) ;
  • Oh, Sung-Kwun (Division of Electrical and Electronic Engineering, Wonkwang Univ.)
  • 발행 : 1998.11.28
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초록

In this paper, we propose the fuzzy inference algorithm with multi-layer structure. MFIS(Multi-layer Fuzzy Inference System) uses PNN(Polynomial Neural networks) structure and the fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Hendling), and uses several types of polynomials such as linear, quadratic and cubic, as well as the biquadratic polynomial used in the GMDH. In the fuzzy inference method, the simplified and regression polynomial inference methods are used. Here, the regression polynomial inference is based on consequence of fuzzy rules with the polynomial equations such as linear, quadratic and cubic equation. Each node of the MFIS is defined as fuzzy rules and its structure is a kind of neuro-fuzzy structure. We use the training and testing data set to obtain a balance between the approximation and the generalization of process model. Several numerical examples are used to evaluate the performance of the our proposed model.

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