Evaluation and Prediction for Thermal-Wet Comfort Properties of Knitting Fabrics Based on Neural Network

Abstract:

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. This paper studied the relationship between knitting fabrics and human comfort from two facets: thermal resistance and water-vapour resistance. The possible physical property indexes to affect thermal-wet comfort were tested, and analyzed by principal component analysis to find the main influence factors. These main influence factors acted as input values of neural network, while thermal resistance and water-vapour resistance acted as output values. The neural network was established and predicted after training. The result showed a considerable relativity. So there had certain accuracy and practical value with neural network model to predict thermal-wet comfort properties of knitting fabrics.

Info:

Periodical:

Edited by:

Yanwen Wu

Pages:

448-451

DOI:

10.4028/www.scientific.net/AMR.187.448

Citation:

J. Li et al., "Evaluation and Prediction for Thermal-Wet Comfort Properties of Knitting Fabrics Based on Neural Network", Advanced Materials Research, Vol. 187, pp. 448-451, 2011

Online since:

February 2011

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Price:

$35.00

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