在对已有成纱质量预测算法进行深入分析后，将关键工艺因素和原棉质量因素作

After in-depth analysis of the existing yarn quality prediction algorithms, the key process factors and raw cotton quality factors are used as input feature factors, three yarn quality prediction methods are designed, and then based on the test results of the three prediction methods, according to the actual situation of the enterprise To build a simple and efficient yarn quality prediction model.

After in-depth analysis of the existing yarn quality prediction algorithm, the key process factors and raw cotton quality factors are designed as input characteristic factors, and three methods of yarn quality prediction are designed, and then based on the test results of the three prediction methods, a simple and efficient analysis of yarn quality prediction model is constructed according to the actual needs of enterprises.

After deeply analyzing the existing yarn quality prediction algorithm, three yarn quality prediction methods are designed with key process factors and raw cotton quality factors as input characteristic factors. Then based on the test results of the three prediction methods, a simple and efficient yarn quality prediction model is constructed according to the actual needs of the enterprise.