地质与资源2026，Vol.35Issue(3)：359-369,378,12.DOI:10.13686/j.cnki.dzyzy.2026.03.013
基于信息量-机器学习耦合的湖南省衡阳市泥石流易发性研究
Susceptibility of debris flow disaster in Hengyang City of Hunan Province based on information value-machine learning coupling model
摘要
Abstract
Taking Hengyang City of Hunan Province as the study area,and selecting the evaluation factors through correlation analysis combined with geographic detector,this paper establishes information value(IV)model with 8 evaluation factors,then constructs the coupling models with random forest(RF)algorithm and light gradient boosting machine(LightGBM)algorithm,respectively,and finally compares the five evaluation models of IV,RF,LightGBM,RF-IV and LightGBM-IV with one another.The ROC curves show that RF-IV model has the highest prediction accuracy compared with the other four models.By comparing the evaluation results of the model with the density distribution data of historical debris flow disaster sites,it is found that the area of high and extremely high susceptible areas accounts for 63.33％of the total.The evaluation results are basically consistent with the actual distribution of debris flow disasters,which can provide reference for subsequent study of debris flow susceptibility as well as prevention and monitoring of debris flow disasters in Hengyang City.关键词
泥石流/地质灾害/信息量模型/随机森林/轻量级梯度提升机/易发性评价/湖南省Key words
debris flow/geological disaster/information value(IV)/random forest(RF)/light gradient boosting machine(LightGBM)/susceptibility evaluation/Hunan Province分类
天文与地球科学引用本文复制引用
邓莉婷,汤军,郭国龙,高贤君,范桂英..基于信息量-机器学习耦合的湖南省衡阳市泥石流易发性研究[J].地质与资源,2026,35(3):359-369,378,12.基金项目
自然资源部环鄱阳湖区域矿山环境监测与治理重点实验室开放基金(MEMI-2021-2022-08) （MEMI-2021-2022-08）
湖南科技大学测绘遥感信息工程湖南省重点实验室开放基金(E22133、E22205) （E22133、E22205）
国家重点研发计划项目(2021YFD1300500). （2021YFD1300500）
