Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/33758
Title: Function estimation using a neural-fuzzy network and an improved genetic algorithm
Authors: Lam, HK
Ling, SH
Leung, FHF 
Tam, PKS
Issue Date: 2004
Publisher: Elsevier Science Inc
Source: International journal of approximate reasoning, 2004, v. 36, no. 3, p. 243-260 How to cite?
Journal: International Journal of Approximate Reasoning 
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.
URI: http://hdl.handle.net/10397/33758
ISSN: 0888-613X
DOI: 10.1016/j.ijar.2003.10.008
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