A comparative prediction for tensile properties of ternary blended open-end rotor yarns using regression and neural network models


ERBİL Y. , BABAARSLAN O. , İLHAN İ.

JOURNAL OF THE TEXTILE INSTITUTE, vol.109, no.4, pp.560-568, 2018 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 109 Issue: 4
  • Publication Date: 2018
  • Doi Number: 10.1080/00405000.2017.1361164
  • Title of Journal : JOURNAL OF THE TEXTILE INSTITUTE
  • Page Numbers: pp.560-568

Abstract

This study focused on predicting tensile properties of PES/CV/PAN blended Open-End Rotor yarns. The effective factors were fiber blend ratios (six stages from 0 to 100%), linear density (three count levels), mixing method (carding machine and drawframe), and number of passages in drawframe (one and two times) as production parameters. We performed a stepwise multiple linear regression (MLR) analysis and established an artificial neural network (ANN) model that trained with backpropagation rule as Levenberg-Marquardt. Then, we conducted a comparative analysis for both models in terms of prediction performance. As a result, ANN has given a slightly better prediction values than MLR for breaking strength but significantly better prediction values for breaking elongation.