长江科学院院报2024，Vol.41Issue(6)：150-155,6.DOI:10.11988/ckyyb.20230595
基于Eclat算法的八字门滑坡变形因素关联性分析
Association Rules of Deformation Factors of Bazimen Landslide Based on Eclat Algorithm
摘要
Abstract
In addressing the substantial data volume within landslide monitoring databases and the lengthy process-ing times due to multiple database scans required for association rule analysis,we introduce the Eclat association rule algorithm into landslide monitoring data mining.This approach involves analyzing the deformation of the Bazi-men landslide using the K-means clustering method and the Eclat algorithm.Through comprehensive investigation,we identify six factors from rainfall monitoring values and reservoir water level monitoring values for data mining and analysis.By uncovering the correlations of three rainfall factors and three reservoir water level factors with the dis-placement of multiple measurement points in the Bazimen landslide,we extract eight association rules with a high confidence level from all excavated correlation rules derived from the spatiotemporal monitoring big data of the Bazi-men landslide.This analysis reveals effective information of rainfall and water level influencing landslide movement.The findings indicate the potential widespread applicability of this data mining method due to its high accuracy in monitoring data research,particularly in the analysis and prediction of accumulation landslides within reservoir areas.关键词
八字门滑坡/Eclat算法/关联规则/数据挖掘/三峡库区Key words
Bazimen landslide/Eclat algorithm/association rules/data mining/Three Gorges Reservoir area分类
天文与地球科学引用本文复制引用
李明亮,吕梅洁,侯梦媛,朱昊..基于Eclat算法的八字门滑坡变形因素关联性分析[J].长江科学院院报,2024,41(6):150-155,6.基金项目
河北省重点研发计划项目(22375415D) （22375415D）
2023年河北省硕士在读研究生创新能力培养项目(CXZZSS2023131) （CXZZSS2023131）
