Application of artificial neural network (ANN) for the prediction of thermal resistance of knitted fabrics at different moisture content

Kanat Z. E., ÖZDİL N.

JOURNAL OF THE TEXTILE INSTITUTE, vol.109, no.9, pp.1247-1253, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 109 Issue: 9
  • Publication Date: 2018
  • Doi Number: 10.1080/00405000.2017.1423003
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1247-1253
  • Keywords: Thermal resistance, artificial neural network, knitted fabric, moisture content, prediction
  • Çanakkale Onsekiz Mart University Affiliated: No


Thermal resistance of the fabrics is one of the decisive parameters in terms of comfort; however it can change due to wetting. Therefore, thermal resistance of wetted fabric is important for comfort performance of garments. In recent years, artificial neural networks (ANN) have been used in the textile field for classification, identification, prediction of properties and optimization problems. ANNs can predict the fabric thermal properties by considering the influence of all fabric parameters at the same time. In this study, ANNs were used to predict thermal resistance of wetted fabrics. For this aim, two different architectures were experienced and high regression coefficient (R-2) between the predicted (training and testing) and observed thermal resistance values were obtained from both models. The obtained regression coefficient values were over 90% for both models. Then it can be said that ANNs could be used for predicting thermal resistance of wetted fabrics successfully.