• DocumentCode
    114302
  • Title

    Critical observations in a diagnostic problem

  • Author

    Christopher, Cody James ; Cordier, Marie-Odile ; Grastien, Alban

  • Author_Institution
    Artificial Intell. Group, Australian Nat. Univ., Canberra, ACT, Australia
  • fYear
    2014
  • fDate
    15-17 Dec. 2014
  • Firstpage
    382
  • Lastpage
    387
  • Abstract
    We claim that presenting a human operator in charge of repairing a faulty system with a small subset of observations relevant to the failure improves awareness and confidence of the operator. Consequently, we introduce the problem of finding a set of relevant observations (called the critical observations) that can be used to derive the same diagnosis as the full problem. We show how this problem can be solved and illustrate its benefits on a real diagnostic problem.
  • Keywords
    power engineering computing; power system faults; critical observation; diagnostic problem; faulty system; Computational modeling; Conferences; Context; Electricity; Government; Sensor systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-1-4799-7746-8
  • Type

    conf

  • DOI
    10.1109/CDC.2014.7039411
  • Filename
    7039411