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Prediction of Drape Coefficient by Artificial Neural Network

Prediction of Drape Coefficient by Artificial Neural Network Abstract An artificial neural network (ANN) model was developed to predict the drape coefficient (DC). Hanging weight, Sample diameter and the bending rigidities in warp, weft and skew directions are selected as inputs of the ANN model. The ANN developed is a multilayer perceptron using a back-propagation algorithm with one hidden layer. The drape coefficient is measured by a Cusick drape meter. Bending rigidities in different directions were calculated according to the Cantilever method. The DC obtained results show a good correlation between the experimental and the estimated ANN values. The results prove a significant relationship between the ANN inputs and the drape coefficient. The algorithm developed can easily predict the drape coefficient of fabrics at different diameters. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Autex Research Journal de Gruyter

Prediction of Drape Coefficient by Artificial Neural Network

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Publisher
de Gruyter
Copyright
Copyright © 2015 by the
ISSN
2300-0929
eISSN
2300-0929
DOI
10.1515/aut-2015-0045
Publisher site
See Article on Publisher Site

Abstract

Abstract An artificial neural network (ANN) model was developed to predict the drape coefficient (DC). Hanging weight, Sample diameter and the bending rigidities in warp, weft and skew directions are selected as inputs of the ANN model. The ANN developed is a multilayer perceptron using a back-propagation algorithm with one hidden layer. The drape coefficient is measured by a Cusick drape meter. Bending rigidities in different directions were calculated according to the Cantilever method. The DC obtained results show a good correlation between the experimental and the estimated ANN values. The results prove a significant relationship between the ANN inputs and the drape coefficient. The algorithm developed can easily predict the drape coefficient of fabrics at different diameters.

Journal

Autex Research Journalde Gruyter

Published: Dec 1, 2015

References