2004 | OriginalPaper | Buchkapitel
Information Granulation-Based Multi-layer Hybrid Fuzzy Neural Networks: Analysis and Design
verfasst von : Byoung-Jun Park, Sung-Kwun Oh, Witold Pedrycz, Tae-Chon Ahn
Erschienen in: Computational Science - ICCS 2004
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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In this study, a new architecture and comprehensive design methodology of genetically optimized Hybrid Fuzzy Neural Networks (gHFNN) are introduced and a series of numeric experiments are carried out. The gHFNN 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 gHFNN. The consequence part of the gHFNN is designed using PNN.