该方法根据纱线各质量指标与关键工艺因素、原棉质量因素的关联度系数，选出

This method selects the influencing factors with larger coefficients as the input variables of the model according to the correlation coefficients of yarn quality indicators with key process factors and raw cotton quality factors, so as to improve the linear correlation between input variables and output variables Small errors in forecast data, improve the accuracy of forecast data.

Based on the correlation coefficient between each quality index of yarn and key process factors and raw cotton quality factors, this method selects the influencing factorwiths with large coefficients as the input variables of the model, so as to improve the linear correlation between the input variables and the output variables, reduce the error of the prediction data and improve the accuracy of the prediction data.

According to the correlation coefficient of yarn quality index, key process factors and raw cotton quality factors, the influential factors with larger coefficient are selected as the input variables of the model, so as to improve the linear correlation between input variables and output variables, reduce the error of prediction data and improve the accuracy of prediction data.