Deciphering decision-making mechanisms for the susceptibility of different slope geohazards:A case study on a SMOTE-RF-SHAP hybrid model  

作　　者：Junhao Huang Haijia Wen Jiwei Hu Bo Liu Xinzhi Zhou Mingyong Liao 

机构地区：[1]School of Civil Engineering,Key Laboratory of New Technology for Construction of Cities in Mountain Area of the Ministry of Education,Chongqing University,Chongqing,400045,China [2]State Key Laboratory of Hydroscience and Engineering,Department of Hydraulic Engineering,Tsinghua University,Beijing,China

出　　处：《Journal of Rock Mechanics and Geotechnical Engineering》2025年第3期1612-1630,共19页岩石力学与岩土工程学报(英文)

基　　金：the National Key Research and Development Program of China(Grant No.2023YFC3007203).

摘　　要：Different slope geohazards have different causal mechanisms.This study aims to propose a method to investigate the decision-making mechanisms for the susceptibility of different slope geohazards.The study includes a geospatial dataset consisting of 1203 historical slope geohazard units,including slope creeps,shallow slides,rockfalls and debris flows,and 584 non-geohazard units,and 22 initial condition factors.Following a 7:3 ratio,the data were randomly divided into a test set and a training set,and an ensemble SMOTE-RF-SHAP model was constructed.The performance and generalization ability of the model were evaluated by confusion matrix and the receiver operating characteristic(ROC)for the four types of geohazards.The decision-making mechanism of different geohazards was then identified and investigated using the Shapley additive explanations(SHAP)model.The results show that the hybrid optimization improves the overall accuracy of the model from 0.486 to 0.831,with significant improvements in the prediction accuracy for all four types of slope geohazards,as well as reductions in misclassification and omission rates.Furthermore,this study reveals that the main influencing factors and spatiotemporal distribution of different slope geohazards exhibit high similarity,while the impacts of individual factors and different factor values on different slope geohazards demonstrate significant differences.For example,prolonged continuous rainfall can erode rock masses and lead to slope creep,increased rainfall may trigger shallow mountain landslides,and sudden surface runoff can even cause debris flows.These findings have important practical implications for slope geohazards risk management.

关 键 词：Random forest Machine learning SMOTE Slope geohazards 

分 类 号：P69[天文地球—地质学]