• DocumentCode
    3065149
  • Title

    Hybrid Intelligent Diagnosis Systems

  • Author

    Chohra, Amine ; Kanaoui, Nadia ; Madani, Kurosh

  • Author_Institution
    Paris XII Univ., Lieusaint
  • fYear
    2007
  • fDate
    28-30 June 2007
  • Firstpage
    115
  • Lastpage
    120
  • Abstract
    In this paper, the main objective is to give a methodology to design hybrid intelligent diagnosis systems for a large field of biomedicine and industrial applications. At first, a brief description on diagnosis tasks in such applications is presented. Second, diagnosis systems are presented. Third, the main steps of hybrid intelligent diagnosis systems are developed, for each step emphasizing problems and suggesting solutions able to ensure the design of hybrid intelligent diagnosis systems with a satisfactory reliability degree. In fact, the main steps discussed are knowledge representation, classification, classifier issued information fusion, and decision-making. Finally, a discussion is given with regard to the suggested methodology.
  • Keywords
    fault diagnosis; knowledge representation; pattern classification; biomedicine applications; decision-making; hybrid intelligent diagnosis systems; industrial applications; information fusion; knowledge classification; knowledge representation; reliability degree; Application software; Biological neural networks; Biomedical computing; Computer networks; Decision making; Fault diagnosis; Fuzzy logic; Hybrid intelligent systems; Intelligent systems; Knowledge representation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Information Systems and Industrial Management Applications, 2007. CISIM '07. 6th International Conference on
  • Conference_Location
    Minneapolis, MN
  • Print_ISBN
    0-7695-2894-5
  • Type

    conf

  • DOI
    10.1109/CISIM.2007.36
  • Filename
    4273506