中国钼业2026，Vol.50Issue(4)：60-65,6.DOI:10.13384/j.cnki.cmi.1006-2602.2026.04.008
基于支持向量机模型的某铜矿回收率预测研究
Prediction of recovery rate in a copper mine based on a support vector machine model
摘要
Abstract
To investigate the influence of various factors in the copper roughing process on copper recovery and establish an accurate prediction model,single-factor and orthogonal experiments were conducted on chalcopyrite flotation.A support vector machine(SVM)model was applied to predict the copper recovery.Single-factor tests showed that under the conditions of Na2S dosage of 110 g/t,butyl xanthate of 55 g/t,ester-205 of 28 g/t,and 2# oil of 45.5 g/t,the copper grade and recovery in the rough concentrate reached 7.15％and 95.23％,respectively.Key influencing factors were identified through orthogonal experiments and range analysis,and an SVM pre-diction model was constructed.The results indicated that the trained model achieved a coefficient of determination(R2)of 0.988 7,good fitting performance.The mean absolute error between the predicted and actual recovery values in 16 validation tests was 0.117 3％,indicating that the prediction accuracy meets the required standards.This study confirms that the SVM model can effectively predict copper recovery,providing valuable guidance for optimizing the flotation process and predicting recovery in chalcopyrite roughing opera-tions.关键词
黄铜矿/SVM模型/铜回收率/浮选Key words
chalcopyrite/SVM model/copper recovery/flotation分类
矿业与冶金引用本文复制引用
彭祥玉,赵椒嵘,张钰,吴忠意,王宇斌..基于支持向量机模型的某铜矿回收率预测研究[J].中国钼业,2026,50(4):60-65,6.基金项目
陕西省科技厅青年基金(编号:2024JC-YBQN-0389) （编号:2024JC-YBQN-0389）
陕西省科学技术协会青年人才托举计划项目(编号:20250403) （编号:20250403）
