Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1361
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Title: Gain estimation for an AC power line data network transmitter using a self-structured neural network and genetic algorithm
Authors: Lam, HK
Ling, SH
Leung, FHF 
Tam, PKS
Lee, YS
Issue Date: 2002
Source: IECON-2002 : Sevilla, Spain, November 5-8, 2002 : proceedings of the 2002 28th Annual Conference of the IEEE Industrial Electronics Society, p. 1926-1929
Abstract: This paper presents the estimation of the transmission gain for the AC power line data network in an intelligent home. The estimated gain ensures the transmission reliability and efficiency. A neural network with link switches is proposed to perform the estimation. Genetic algorithm with arithmetic crossover and non-uniform mutation is employed to tune the parameters and the structure of the proposed neural network. An application example will be given.
Keywords: Distributed parameter control systems
Gain control
Genetic algorithms
Neural networks
Power control
SCADA systems
Publisher: IEEE
ISBN: 0-7803-7474-6
Rights: © 2002 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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