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

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

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

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.
Original languageEnglish
Title of host publicationIEEE International Conference on Fuzzy Systems
Pages167-172
Number of pages6
Publication statusPublished - 11 Jul 2003
EventThe IEEE International conference on Fuzzy Systems - St. Louis, MO, United States
Duration: 25 May 200328 May 2003

Conference

ConferenceThe IEEE International conference on Fuzzy Systems
CountryUnited States
CitySt. Louis, MO
Period25/05/0328/05/03

ASJC Scopus subject areas

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

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