한국지능시스템학회논문지 (Journal of the Korean Institute of Intelligent Systems)

  • 제14권5호
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  • Pages.660-665
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  • 2004
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  • 1976-9172(pISSN)
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  • 2288-2324(eISSN)
한국지능시스템학회 (Korean Institute of Intelligent Systems)
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The Design of Genetically Optimized Multi-layer Fuzzy Neural Networks

  • Park, Byoung-Jun (School of Electrical, Electronic and Information Engineering, Wonkwang University) ;
  • Park, Keon-Jun (School of Electrical, Electronic and Information Engineering, Wonk wang University, Kore) ;
  • Lee, Dong-Yoon (Department of Information and Communication Engineering, Joongbu University, Kore) ;
  • Oh, Sung-Kwun (School of Electrical, Electronic and Information Engineering, Wonkwang University)
  • 발행 : 2004.08.01
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초록

In this study, a new architecture and comprehensive design methodology of genetically optimized Multi-layer Fuzzy Neural Networks (gMFNN) are introduced and a series of numeric experiments are carried out. The gMFNN architecture results from a synergistic usage of the hybrid system generated by combining Fuzzy Neural Networks (FNN) with Polynomial Neural Networks (PNN). FNN contributes to the formation of the premise part of the overall network structure of the gMFNN. The consequence part of the gMFNN is designed using PNN. The optimization of the FNN is realized with the aid of a standard back-propagation learning algorithm and genetic optimization. The development of the PNN dwells on the extended Group Method of Data Handling (GMDH) method and Genetic Algorithms (GAs). To evaluate the performance of the gMFNN, the models are experimented with the use of a numerical example.

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참고문헌

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