Title :
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
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;
Conference_Titel :
Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
Print_ISBN :
0-7803-7810-5
DOI :
10.1109/FUZZ.2003.1209356
