THE PREDICTION OF COTTON YARN IRREGULARITY BASED ON THE AFIS MEASUREMENT

This paper presents a neural network model for predicting the yam irre gularity, based on inputs of fiber property measurements with the AFIS instrument. By using a back-propagation neural network algorithm, alt ernative models were fitted and compared. The resulting predictions of yarn irregularity are superior to these obtained by using conventiona l multiple-linear regression techniques.