Modelling the breaking strength of PC blends rotor spun yarn.

Abstract

In this study, SVM as a new intelligent methodology was applied to obtain a predictive model of strength of polyester cotton rotor spun yams based on three main parameters; the rotor speed, the count and blend ratio. And linear regression model was also used in my study as a criterion to evaluate the predictive power of the SVM algorithm. Obtained results from the tests of the study indicated a powerful performance of the linear regression programming algorithm in predicting the strength of rotor spun yarns with the R2 values of the SVM model and linear regression model were 27.74% and 99.97% respectively. Other relations are showed in the table III. The 27.74% value of R2 of the SYM shows a very weak relationship between the actual and predicted values as it is less than 50% and hence conclusively, the SVM model for predicting yarn strength was modelled.