• DocumentCode
    2830060
  • Title

    Decision-making in an energy system: a knowledge-based solution

  • Author

    Boukerche, Kaddour ; Lounis, Hakim

  • Author_Institution
    Dept. of Comput. Sci., Univ. de Sherbrooke, Que., Canada
  • fYear
    2005
  • fDate
    16-18 Aug. 2005
  • Firstpage
    144
  • Lastpage
    151
  • Abstract
    The present work is about a solution implementing a decision-making system in the management of production of a hydroelectric network. An object-oriented rule-based architecture is proposed to ensure an intelligent and automatic management of the knowledge in use in this daily decisional process. An alternate planner-based solution is also discussed. On the other hand and for improving the forecast of natural contributions flow, we described how we exploit machine-learning techniques, including artificial neural networks.
  • Keywords
    hydroelectric power; knowledge based systems; knowledge management; learning (artificial intelligence); neural nets; object-oriented methods; power engineering computing; power system management; power system planning; artificial neural networks; decision-making; energy system; hydroelectric network; intelligent management; knowledge management; knowledge-based system; machine learning; object-oriented rule-based architecture; production management; Computer network management; Computer science; Decision making; Hydrologic measurements; Knowledge based systems; Object oriented modeling; Power generation; Process planning; Production systems; Weather forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems Engineering, 2005. ICSEng 2005. 18th International Conference on
  • Print_ISBN
    0-7695-2359-5
  • Type

    conf

  • DOI
    10.1109/ICSENG.2005.33
  • Filename
    1562843