Function estimation using a neural-fuzzy network and an improved genetic algorithm

H.K. Lam, S. Ling, F.H.F. Leung, P.K.S. Tam

    Research output: Contribution to journalArticle

    4 Citations (Scopus)

    Abstract

    This paper presents the estimation of the transmission gains for an AC power line data network in an intelligent home. The estimated gains ensure the transmission reliability and efficiency. A neural-fuzzy network with rule switches is proposed to perform the estimation. An improved genetic algorithm is proposed to tune the parameters and the rules of the proposed neural-fuzzy network. By turning on or off the rule switches, an optimal rule base can be obtained. An application example will be given. (C) 2003 Elsevier Inc. All rights reserved.
    Original languageEnglish
    Pages (from-to)243-260
    JournalInternational Journal of Approximate Reasoning
    Volume36
    Issue number3
    DOIs
    Publication statusPublished - 2004

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