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Modelling and Simulation in Engineering
Volume 2011 (2011), Article ID 591905, 8 pages
http://dx.doi.org/10.1155/2011/591905
Research Article

Modelling and Predicting the Breaking Strength and Mass Irregularity of Cotton Rotor-Spun Yarns Containing Cotton Fiber Recovered from Ginning Process by Using Artificial Neural Network Algorithm

Textile Engineering Department, Isfahan University of Technology, Isfahan 84156-83111, Iran

Received 9 March 2011; Accepted 13 April 2011

Academic Editor: Philippe Boisse

Copyright © 2011 Mohsen Shanbeh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [2 citations]

The following is the list of published articles that have cited the current article.

  • Yildiray Turhan, and Ozan Toprakci, “Comparison of high-volume instrument and advanced fiber information systems based on prediction performance of yarn properties using a radial basis function neural network,” Textile Research Journal, vol. 83, no. 2, pp. 130–147, 2013. View at Publisher · View at Google Scholar
  • Yılmaz Erbil, Osman Babaarslan, and İlhami Ilhan, “A comparative prediction for tensile properties of ternary blended open-end rotor yarns using regression and neural network models,” The Journal of The Textile Institute, pp. 1–9, 2017. View at Publisher · View at Google Scholar