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Prediction of Fabrics’ Air Permeability Properties by Artificial Neural Network (ANN) Models



Author(s)

Alev Erenler¹ and R. Tuğrul Oğulata²

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DOI:10.17265/2161-6213/2018.9-10.005

1. Textile, Clothing, Footwear and Leather Department, Gerze Vocational School, Sinop University, Gerze Vocational School, Sinop 57600, Turkey
2. Textile Engineering Department, Engineering And Architecture Faculty, Çukurova University, Textile Engineering Department, Adana 01330, Turkey

In this research it is aimed to predict fabrics’ air permeability properties by ANNs (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 finishing treatments for antipilling were applied to fabrics in 3 concentrations. ANN models were established to predict fabrics’ air permeability values with the selected 6 inputs such as weft yarn number, weft density, weaving pattern, fabric weight, fabric thickness and finishing treatment concentrations. The best results whose regression degree is R = 0.99366, were obtained with two hidden layer networks with 5 neurons.

Air permeability, ANN, prediction, antipilling finishing.