工矿自动化2026，Vol.52Issue(4)：96-104,9.DOI:10.13272/j.issn.1671-251x.18266
基于WMA-LightGBM的露天矿边坡稳定性预测
Slope stability prediction for open-pit mines based on WMA-LightGBM
摘要
Abstract
For slope stability prediction in open-pit mines,traditional physico-mechanical analysis or numerical simulation methods suffer from complex modeling processes and high computational costs,while existing machine learning models show varying sensitivity to different data types and struggle to obtain globally optimal solutions.To address these issues,a slope stability prediction model integrating the Whale Migration Algorithm(WMA)and Light Gradient Boosting Machine(LightGBM),namely the WMA-LightGBM model,was proposed.Six primary controlling factors of slope stability-slope height,slope angle,unit weight,cohesion,internal friction angle,and pore pressure ratio-were selected as model inputs.The dual-stage collaborative optimization and adaptive migration strategy of WMA were employed to perform adaptive global optimization of LightGBM hyperparameters,enabling accurate prediction of slope stability states.Experimental results showed that the WMA-LightGBM model exhibited strong generalization ability,achieved zero missed detections of unstable slopes,and maintained a low misclassification rate for stable slopes.The model attained an accuracy of 96.3％,precision of 100％,recall of 94％,F1-score of 0.968,and an Area Under the Curve(AUC)value of 0.98,significantly outperforming comparative models in both engineering safety and predictive accuracy.Furthermore,feature dependency analysis based on the SHAP algorithm revealed the influence patterns of input features on prediction outcomes,validating the rationality of the model's predictive logic and providing key support for its reliable engineering application in slope stability prediction scenarios.关键词
露天矿/边坡稳定性预测/鲸鱼迁徙优化算法/WMA/轻量级梯度提升机/LightGBMKey words
open-pit mine/slope stability prediction/Whale Migration Algorithm/WMA/Light Gradient Boosting Machine/LightGBM分类
矿业与冶金引用本文复制引用
李山,王文静,白佩云,马彪,李利..基于WMA-LightGBM的露天矿边坡稳定性预测[J].工矿自动化,2026,52(4):96-104,9.基金项目
新疆维吾尔自治区重点研发计划项目(2022B03031-1). （2022B03031-1）
