Prediction of air permeability properties with artificial neural network models of fabrics which applied softness and water repellent finishing treatments

Abstract

In this research it is aimed to predict fabrics' air permeability properties by artificial neural networks before production with using inputs like some fabric parameters and finishing treatments. For this aim 27 various fabrics were weaved. After dyeing, softness and water repellent finishing treatments were applied to fabrics in 3 different concentrations. Artificial neural network models were established to predict fabrics' air permeability values with the selected 7 inputs such as weft yarn number, weft density, weaving pattern, fabric weight, fabric thickness, finishing treatment and finishing treatment concentrations. The best results which regression degree is R=0,99821 were obtained with two hidden layer network with 20 neurons. It also designed an interface for estimation using the matlab gui program.