Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/21851
Title: A new fuzzy approach to improve fashion product development
Authors: Lau, TW
Hui, PCL 
Ng, FSF 
Chan, KCC 
Keywords: Fabric hand descriptors
Fabric specimen prediction
Fuzzy system
Sensory knowledge
Issue Date: 2006
Publisher: Elsevier
Source: Computers in industry, 2006, v. 57, no. 1, p. 82-92 How to cite?
Journal: Computers in industry 
Abstract: This study attempts to use a fuzzy expert system with gradient descent optimization for prediction of fabric specimens in fashion product development. Compared with the traditional methods used fabric mechanical properties to predict fabric specimens, our advisory system accepts fabric hand descriptors which are more closely related to the sensory judgments made by individuals during fabric selection. Fifty participants were selected to evaluate the performance of the proposed fuzzy fabric advisory system. They were asked to express their preferred fabric specimen on inputs of the 14 bipolar fabric hand descriptors in the system. The fuzzy prediction rules associated with the membership functions of each fabric specimen were developed from a survey. After fine-tuning of the proposed system, the prediction accuracy is over eighty percent. The outcomes of this study could help consumers to select the most appropriate fabric and provide field practitioners appropriate suggestions for effective product development in clothing and fashion industries.
URI: http://hdl.handle.net/10397/21851
ISSN: 0166-3615
DOI: 10.1016/j.compind.2005.04.003
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