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
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;
Conference_Titel :
Intelligent Engineering Systems, 1997. INES '97. Proceedings., 1997 IEEE International Conference on
Conference_Location :
Budapest
Print_ISBN :
0-7803-3627-5
DOI :
10.1109/INES.1997.632454
