Prediction of dimensional properties of weft knitted cardigan fabric by artificial neural network system

Abstract

The objective of this paper is to propose an artificial neural network model to predict the dimensional properties of a weft-knitted double cardigan structure made from 100% cotton ring spun yarns. Through experimental study, various U-values (K-constants of derivative knitted structures) were established for the given structure. The factors investigated were yarn count, structural-cell stitch length, course and wale density and stitch density in different relaxation states. A predictive model of artificial neural network was developed with experimental results. Further, the artificial neural network model was compared with U-values established using test set of inputs. The prediction of the dimensional properties produced by the neural network model proved to be highly reliable ( R2 > 0.98).