烟台大学学报（自然科学与工程版）2025，Vol.38Issue(3)：282-290,9.DOI:10.13951/j.cnki.37-1213/n.240508
基于数据挖掘的旧县坪滑坡变形演化特征及主控因素识别
Deformation Evolution Characteristics and Main Control Factors Identification of Jiuxianping Landslide Based on Data Mining
摘要
Abstract
To accurately identify landslide-prone areas and develop timely,effective prevention and control meas-ures,this study explores the deformation evolution characteristics of landslides and identifies their main deformation control factors through analysis of field-measured data.Using Jiuxianping landslide in the Three Gorges reservoir ar-ea as a case study,several monitoring points at different sections of the landslide were selected.The analysis fo-cused on the landslide deformation characteristics and their response to fluctuations in reservoir water levels and rainfall.Based on triggering factors identified in previous studies,dominant triggers were screened,and a two-step clustering method was employed to automatically group landslide displacement rates and impact factors.The Apriori algorithm was then applied to reveal association rules between landslide displacement rates and impact factors,i-dentifying key deformation control factors across different landslide sections.Results indicate significant spatio-tem-poral variations in Jiuxianping landslide deformation.Deformation is more intense in the middle and front sections compared to the rear,with the middle and front displacement-time curves showing a stepped pattern,while the rear follows a shock-type pattern.Primary deformation controll factors vary by locations:the middle and front are influ-enced by both reservoir water levels and rainfall,whereas the rear is more sensitive to rainfall.关键词
数据挖掘/滑坡变形/Apriori算法/关联规则Key words
data mining/landslide deformation/Apriori algorithm/association rule分类
天文与地球科学引用本文复制引用
刘兴瑜,杨背背,夏炳起..基于数据挖掘的旧县坪滑坡变形演化特征及主控因素识别[J].烟台大学学报（自然科学与工程版）,2025,38(3):282-290,9.基金项目
山东省自然科学基金资助项目(ZR2021QD032). （ZR2021QD032）
