Comparison of Regression and Adaptive Neuro-fuzzy Models for Predicting the Bursting Strength of Plain Knitted Fabrics

摘要

The aim of this study was to compare the response surface regression and adaptive neuro-fuzzy models for predicting the bursting strength of plain knitted fabrics. The prediction models are based on the experimental data comprising yarn tenacity, knitting stitch length and fabric GSM as input variables and fabric bursting strength as output/response variable. The models quantitatively characterize the non-linear relationship and interactions between the input and output variables exhibiting very good prediction ability and accuracy, with ANFIS model being slightly better in performance than the regression model.