A fuzzy neural network model for predicting clothing thermal comfort

Authors:
Xiaonan Luo;Wenbang Hou;Yi Li;Zhong Wang
Affiliations:
Computer Application Institute, Sun Yat-sen University, Guang Zhou 510275, China;Computer Application Institute, Sun Yat-sen University, Guang Zhou 510275, China;Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hong Kong;Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hong Kong
Venue:
Computers & Mathematics with Applications
Year:
2007

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Abstract

This paper presents a Fuzzy Neural Network (FNN) based local to overall thermal sensation model for prediction of clothing thermal function in functional textile design system. Unlike previous experimental and regression analysis approaches, this model depends on direct factors of human thermal response - body core and skin temperatures. First the local sensation is predicted by a FNN network using local body part skin temperatures, their change rates, and core temperature as inputs; then the overall sensation is predicted. This is also performed by a FNN network. The FNN networks are developed on the basis of the Feed-Forward Back-Propagation (FFBP) network; the advantage of using fuzzy logic here is to reduce the requirement of training data. The simulation result shows a good correlation between predicted and the traditional experimental data.