• DocumentCode
    1422796
  • Title

    An adaptive fuzzy technique for learning power-quality signature waveforms

  • Author

    Ibrahim, W. R Anis ; Morcos, M.M.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Kansas State Univ., Manhattan, KS, USA
  • Volume
    21
  • Issue
    1
  • fYear
    2001
  • fDate
    1/1/2001 12:00:00 AM
  • Firstpage
    56
  • Lastpage
    58
  • Abstract
    This letter presents a new technique for learning power-quality waveforms. The approach is an intelligent technique based on exploiting the capabilities of adaptive fuzzy logic learning. The development of the mechanism was essential for the completion of an intelligent fuzzy expert system targeting power-quality problems using a mal-operation prediction technique
  • Keywords
    expert systems; fuzzy logic; learning (artificial intelligence); power supply quality; power system analysis computing; adaptive fuzzy logic learning; adaptive fuzzy technique; intelligent fuzzy expert system; intelligent technique; mal-operation prediction technique; power-quality problems; power-quality signature waveforms learning; Adaptive systems; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Hybrid intelligent systems; Intelligent systems; Neural networks; Power quality; System testing;
  • fLanguage
    English
  • Journal_Title
    Power Engineering Review, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1724
  • Type

    jour

  • DOI
    10.1109/39.893344
  • Filename
    893344