ITAST (Iranian Textile Association of Science and Technology) Journal of Textiles and Polymers 2322-5203 7 1 2019 01 01 Applying Fuzzy Logic Model for Bending Rigidity Evaluation of Woven Fabrics 61 68 83100 EN Najmeh Dehghan-Manshadi Textile Department, Faculty of Engineering, Yazd University, Yazd, Iran. Mohsen Hadizadeh Textile Department, Faculty of Engineering, Yazd University, Yazd, Iran. Journal Article 2019 02 27  Fabric bending rigidity evaluation plays a very important role in determining end-use quality of products. This property has a non-linear behavior. Many techniques, such as mathematical, multiple regression, artificial neural network model, etc., have been used to predict mechanical properties of fabrics.  This paper presents a method to model the bending rigidity of plain-woven fabrics using fuzzy logic. The input variables are yarn count, yarn diameter, yarn spacing, yarn bending rigidity and yarn length. The output variable is fabric bending rigidity. These results revealed the efficiency of fuzzy model to predict bending rigidity based on the mentioned parameters. Then the prediction accuracy of fuzzy logic model in comparison with three modeling methodologies based on mathematical, empirical and artificial neural network was evaluated. The comparison of the prediction performance showed that the fuzzy model is more powerful than the other models. http://www.itast.ir/article_83100_7e1ce4ce3124fd9ecc13a151afcff11b.pdf