Predicting strength transfer efficiency of warp and weft yarns in woven fabrics using adaptive neuro-fuzzy inference system

Abstract

The application of adaptive neuro-fuzzy inference system for the prediction of strength transfer efficiencies of warp and weft yarns in woven fabrics has been studied. The developed neuro-fuzzy models are based on the input-output data sets of 264 woven fabric samples, out of which the data of 234 samples are used for developing the prediction models while data of 30 samples are used for models’ validation. The developed models are capable of predicting the warp and weft yarns strength transfer efficiencies quite accurately, given the strength of constituent yarns, the fabric count and the float length.