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

. 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, Q. Liu, L. B. Xia, "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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