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

Publication Type:
Journal Article
International Journal of Approximate Reasoning, 2004, 36 (3), pp. 243 - 260
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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. © 2003 Elsevier Inc. All rights reserved.
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