Gain estimation for an AC power line data network transmitter using a neural-fuzzy network and an improved genetic algorithm

Author

Lam, H.K. ; Ling, S.H. ; Leung, F.H.F. ; Tam, P.K.S. ; Lee, Y.S.

Author_Institution

Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., Kowloon, China

Volume

1

fYear

2003

Firstpage

167

Abstract

This paper presents the estimation of the transmission gain for an AC power line data network in an intelligent home. The estimated gain ensures 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.

Keywords

building management systems; fuzzy neural nets; genetic algorithms; home automation; power transmission reliability; AC power line data network; fuzzy associative memory; improved genetic algorithm; intelligent home; neural-fuzzy network; optimal rule base; rule switches; transmission efficiency; transmission gain estimation; transmission reliability; transmitter gain; Communication channels; Communication system control; Electrical products; Electromagnetic interference; Genetic algorithms; Home appliances; Intelligent networks; Intelligent systems; Neurotransmitters; Switches;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on

Print_ISBN

0-7803-7810-5

Type

conf

DOI

10.1109/FUZZ.2003.1209356

Filename

1209356