Prediction of the Wearing Comfort Performance of Tight-fitting Garment by Optimization ANN

摘要：

The predictions are based on fabric mechanical properties measured on the KES system. In order to select the efficient input variables of ANN （artificial neural network ）during the prediction of wearing comfort performance grey incidence (GI)analysis, as a mathematic method that ranks the sequence of importance of lots of variables in complicated factors has been applied. The optimization ANN models with the parameters selected by using the GI analysis are investigated, which construct on the convergence speed and the prediction accuracy The result indicates that the optimization model of BP neural network is an efficiency technique and has a wide prospect in the application to prediction of wearing comfort performance.

关键词： wearing comfort performance optimization model fabric mechanical performance

作者: CONG Shan ZHANG Weiyuan

作者单位: Shanghai University of Engineering Science, Shanghai, China;Fashion Institute, Donghua University, S Fashion Institute, Donghua University, Shanghai, China

会议类型: 国际会议

会议名称: 第七届国际测试技术研讨会

会议地点: 北京

会议语种:英文

在线出版日期: 2007-08-05（万方平台首次上网日期，不代表论文的发表时间）