| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 509603 | Computers in Industry | 2006 | 11 Pages |
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.
