• DocumentCode
    1630942
  • Title

    Automatic parameter tuning of stochastic qualitative model of building air conditioning systems

  • Author

    Yamasaki, Takahiro ; Yumoto, Masaki ; Ohkawa, Takenao ; Komoda, Norihisa ; Miyasaka, Fusachilta

  • Author_Institution
    Dept. of Inf. Syst. Eng., Osaka Univ., Japan
  • fYear
    1997
  • Firstpage
    415
  • Lastpage
    420
  • Abstract
    We have proposed the stochastic qualitative simulation which can derive approximate behavior from a simple qualitative model of a target. In this method, the model must be constructed with numerous stochastic parameters. The parameter tuning process is the most difficult element of model construction. This paper outlines an automatic parameter turning by means of the steepest ascent based method. This method was used in order to generate a model of a real air conditioning system in a building
  • Keywords
    air conditioning; inference mechanisms; probability; stochastic processes; temperature control; tuning; air conditioning systems; automatic parameter tuning; building; probability; steepest ascent method; stochastic qualitative model; stochastic qualitative reasoning; temperature control; Air conditioning; Buildings; Computational modeling; Fluid flow measurement; Humans; Information systems; Stochastic processes; Stochastic systems; Systems engineering and theory; Turning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Engineering Systems, 1997. INES '97. Proceedings., 1997 IEEE International Conference on
  • Conference_Location
    Budapest
  • Print_ISBN
    0-7803-3627-5
  • Type

    conf

  • DOI
    10.1109/INES.1997.632454
  • Filename
    632454