机械制造与自动化2026，Vol.55Issue(4)：19-23,38,6.DOI:10.19344/j.cnki.issn1671-5276.2026.04.004
基于MIC-RF随机森林的热轧带钢力学性能预测
Prediction of Mechanical Properties of Hot-rolled Strip Steel Based on MIC-RF Algorithm
摘要
Abstract
To meet the increasing requirements for prediction accuracy of mechanical properties of hot-rolled strip steea prediction model for the mechanical properties of hot-rolled strip steel was constructed based on the the MIC-RF method,with yield strength(Re)and tensile strength(Rm)as the research objects.The Pauta criterion was used to preprocess the actual hot-rolling data and remove outliers.The maximum mutual information coefficient method(MIC)was employed to screen important influencing features as input variables for the model.The random forest algorithm was used to train the model and was compared with a random forest model without feature selection.It is shown that the prediction errors for Re and Rm based on the MIC-RF are both less than 1%,with coefficients of determination above 0.99,and tthe prediction accuracy is superior to that of the random forest model without feature selection.The proposed model has higher prediction accuracy and strong generalization ability,providing an intuitive and reliable reference for the design and optimization of strip steel products.关键词
MIC最大互信息系数/RF随机森林/热轧带钢/力学性能预测Key words
MIC(maximum mutual information coefficient)/RF(random forest)/hot-rolled steel/mechanical property prediction分类
矿业与冶金引用本文复制引用
王力,朱启宁,杨洪凯,张磊..基于MIC-RF随机森林的热轧带钢力学性能预测[J].机械制造与自动化,2026,55(4):19-23,38,6.基金项目
国家自然科学基金资助项目(U21A20117) （U21A20117）
辽宁省人工智能领域科技创新项目(重大专项项目)(2023JH26/10100002) （重大专项项目）
中国五矿科技专项项目(2022ZXB03) （2022ZXB03）
