Abstract
Engineered fabric manufacturing needs a thorough understanding of the functional properties and their key control construction parameters. When the relationship between a set of interrelated properties goes beyond the complete comprehension of the human brain, neural networks (NNs) could be used to find the unknown function. This study describes the method of applying artificial NNs for the prediction of both construction and performance parameters of canopy fabrics. Based on the influence on the performance of the canopy fabric, constructional parameters are chosen. Accordingly, constructional parameters are used as input for predicting the performance parameter in forward engineering, and the parameters are reversed for the reverse engineering prediction. Comparison between actual results and predicted results is made. An expert system with an embedded artificial neural network (ANN) is also discussed, with its functionality toward engineered fabric manufacturing. © 2006 Sage Publications.
Author supplied keywords
Cite
CITATION STYLE
Behera, K. B., & Karthikeyan, B. (2006). Artificial neural network-embedded expert system for the design of canopy fabrics. Journal of Industrial Textiles, 36(2), 111–123. https://doi.org/10.1177/1528083706067684
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.