Intelligent modelling of the indoor climate in buildings by soft computing

The paper considers the application of soft computing techniques for predictive modelling in the built sector. TakagiSugeno fuzzy models are built by subtractive clustering to provide initial values of the antecedent non-linear membership functions parameters and the consequent linear algebraic equations coefficients. A method of extensive searching the possible fuzzy model structures is presented which explores all the possible permutations for a specified range of orders to derive the initial fuzzy model. The model parameters are further adjusted by a back-propagation neural network and a real-valued genetic algorithm in order to obtain a better fit to the measured data.

• Type: Conference
• Year: 2001
• Where: EUSFLAT
• Authors: Alexander Gegov
• Keywords: EUSFLAT 2001, EUSFLAT 2007, Fuzzy Model, Initial Fuzzy Model, Possible Fuzzy Model