Prediction of Fabric End-use Using a Neural Network Technique
Document Type
Article
Publication Date
1-1-2001
Abstract
A neural network computing technique was proposed to predict fabric end-use. One hundred samples of apparel fabrics were selected and measured using the Kawabata KES-FB instruments. Instrumental data of the fabric properties and information on fabric end-uses, suitings shirts, and blouses, were input into a neural network software to train a multilayer perceptron model. The prediction error rate from the established neural network model was estimated by using a cross-validation method. © 2001 Taylor & Francis Group, LLC.
Publication Source (Journal or Book title)
Journal of the Textile Institute
First Page
157
Last Page
163
Recommended Citation
Chen, Y., Zhao, T., & Collier, B. (2001). Prediction of Fabric End-use Using a Neural Network Technique. Journal of the Textile Institute, 92 (2), 157-163. https://doi.org/10.1080/00405000108659567