Yarn Strength Prediction Using Neural Networks

Abstract

Over the past several years, numerous relationships between fiber properties and yarn performance have been developed. The classical method for predicting yam performance is statistical analysis such as linear multiple regression. Neural networks are now a subject of interest in many fields and a tool for many areas of problem solving. This study investigates the application of neural networks to yarn strength prediction. HVI test results of the 1989 crop are used to train the neural nets and performance is discussed.