基于机器学习的纺织品洗液沾色程度AI评估模型构建OA

To address the challenges in emerging textile washing solution staining evaluation,such as the lack of standardized methods,high subjectivity,low efficiency,and unquantifiable differences caused by reliance on visual inspec-tion,a feature optimization strategy that integrates mutual information,Pearson correlation coefficient,and multi-algorithm joint screening is proposed.By comparing six machine learning models with dE(color difference)as the key feature,the K-nearest neighbors(KNN)model achieves an accuracy of 92%.This model not only provides a reliable solution for assessing the degree of textile washing solution staining,but also enables the transition from conventional visual-based evaluation to automated model-driven grading,significantly enhancing objectivity and operational efficiency in industrial applications.