Evaluation of Clothing Comfort Using Neural Networks

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To assess clothing comfort quantitatively, we carried out wear trials with cotton, polyester and modified polyester and evaluated their clothing comfort using three-layered neural networks by the back propagation method. It was confirmed that clothing comfort was precisely predictable using neural networks from the height of generalizing ability. The differences among cotton, polyester and modified polyester were observed as the differences in generalizing abilities and weight coefficients in this system and the effects of clothing material on clothing comfort were made dear using this neural networks. It was also found that evaluation by neural networks was very useful for even an object which was difficult to model exactly, such as wear trial.