水力发电学报2025，Vol.44Issue(5)：125-132,8.DOI:10.11660/slfdxb.20250511
聚类-自组织神经网络变点分析确定边坡失稳判据研究
Define instability criterion of slope by change point analysis of cluster self-organizing maps
摘要
Abstract
The strength reduction method is widely used for slope stability analysis,and different instability criteria have their own characteristics.Among them,a simple and practical one is the mutation in the displacement reduction coefficient curve.This study uses cluster analysis to select the displacement mutation feature point,and identifies its mutation using the self-organizing neural network change point analysis method.Then,we suggest an improved criterion for this mutation.Such a fusion method is more objective and mathematically based.For typical examples,safety factors calculated by this analysis method are closer to the recommended values than those of the strength reduction method used in FLAC3D.关键词
边坡/聚类分析/自组织神经网络/变点分析/强度折减法Key words
slope/clustering analysis/self-organizing neural network/change-point analysis/strength reduction method分类
土木建筑引用本文复制引用
李伟瀚,雷从雨,介玉新,张彬..聚类-自组织神经网络变点分析确定边坡失稳判据研究[J].水力发电学报,2025,44(5):125-132,8.基金项目
国家自然科学基金重大项目(52090081 （）
41790434) （）
