Engineering design of polyester-viscose blended suiting fabrics using radial basis function network: Part I — Prediction of fabric low-stress mechanical properties

Abstract

A complete engineering design of polyester-viscose blended suiting fabrics has been presented using radial basis function neural network algorithm. Fabric low-stress mechanical properties, such as extension, bending rigidity, shear rigidity, breaking strength have been predicted from the structural parameters of the fabric such as weave, yarn tex, thread

density, crimp, fabric mass and fabric cover. It is observed that the radial basis function neural network could successfully predict the trends in variation of fabric property with corresponding change in structural parameters.