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

H. K. Lam, S. H. Ling, Hung Fat Frank Leung, P. K.S. Tam

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)243-260
Number of pages18
JournalInternational Journal of Approximate Reasoning
Volume36
Issue number3
DOIs
Publication statusPublished - 1 Jul 2004

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

Cite this