The Contrast between Multiple Linear Regression and Artificial Neural Network for Wool Worsted Weaving Forecasting

The neural network technology and multiple linear regression used to weaving process of wool worsted were introduced in this paper. The main jobs for setting up two kinds of forecast models by these two methods for weaving process were put forward. And also the models to predict the loom efficiency was given. After that the character of the neural network and multiple linear regression models were demonstrated and contrasted by the forecast results, and the contrast between these two models for solving the nonlinear and linear problems was shown. And the linear or nonlinear relationships between the yarn quality and weaving parameters and woven quality indexes were also given.