应用数学和力学2026，Vol.47Issue(1)：32-45,14.DOI:10.21656/1000-0887.460102
基于数值模拟和决策树回归的金属切削力学性能预测
Mechanical Property Prediction of Metal Cutting Based on Numerical Simulation and Decision Tree Regression
摘要
Abstract
Rapid prediction of mechanical properties of metal cutting is critical to optimal design and productiv-ity improvement of industrial manufacturing.Current prediction models often require expensive and time-consu-ming experimental and analytical processes.A prediction model based on metal cutting simulation and decision tree regression was constructed to obtain mechanical properties under different cutting conditions.Firstly,the adaptive smoothed particle hydrodynamics(ASPH)was used to simulate the metal cutting process,capture a variety of mechanical properties under different simulation parameters,and form a simulation dataset of 2 000 cutting conditions.Secondly,the decision tree regression(DTR)was used to learn the simulation data set,train and construct the metal cutting prediction model,and evaluate the effect of the prediction model under different pruning strategies by cross-validation and grid search.The results show that,the established predic-tion model can quickly predict multi-mechanical properties under different simulation parameters,and the ap-propriate pruning strategy can improve the accuracy,generalization ability and stability of the prediction model.关键词
金属切削/力学性能预测/数值模拟/自适应光滑粒子流体动力学/决策树回归Key words
metal cutting/mechanical property prediction/numerical simulation/adaptive smoothed particle hydrodynamics/decision tree regression分类
数理科学引用本文复制引用
程一晋,冯志强,李燕..基于数值模拟和决策树回归的金属切削力学性能预测[J].应用数学和力学,2026,47(1):32-45,14.基金项目
国家自然科学基金(12372142 （）
12572232) （）
