Title :
Prediction of Fabric Subjective Thermal-Wet Comfort Properties by Inputting the Objective Parameters
Author_Institution :
Fashion Inst., Shanghai Univ. of Eng. Sci., Shanghai, China
Abstract :
In this paper, the dynamic thermal-wet comfort objective evaluation indexes such as KTs, KTe, Tequ, ΔT and RHequ of 36 kinds of knitted fabrics were tested. And then the 36 kinds of knitted fabrics were made into clothes of same style. The thermal-wet comfort subjective evaluation indexes such as hot feeling, wet feeling, sticky feeling and cold feeling after exercise of these clothes were assessed by human body wearing tests. 28 kinds of the fabrics were selected to establish the prediction model between the objective and subjective evaluation indexes based on BP neural network. The other 8 kinds of fabrics were used to validate the accuracy of the model. The results showed that the model can effectively predict the subjective thermal-wet comfort properties of fabrics.
Keywords :
backpropagation; fabrics; neural nets; prediction theory; production engineering computing; woven composites; BP neural network; cold feeling; dynamic thermal wet comfort objective evaluation index; fabric subjective thermal wet comfort property; hot feeling; human body wearing test; knitted fabrics; prediction model; sticky feeling; wet feeling; Accuracy; Artificial neural networks; Fabrics; Indexes; Predictive models; Testing; Training; BP neural network; objective thermal-wet comfort; prediction; subjective thermal-wet comfort;
Conference_Titel :
Network Computing and Information Security (NCIS), 2011 International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-61284-347-6
DOI :
10.1109/NCIS.2011.115
