防灾减灾工程学报2025，Vol.45Issue(5)：1052-1061,10.DOI:10.13409/j.cnki.jdpme.20250612001
基于主动学习支持向量机的预应力锚索加固边坡可靠度分析
Reliability Analysis of Slopes Reinforced with Prestressed Anchor Cables Based on Active Learning Support Vector Machine
摘要
Abstract
The reservoir bank slopes of high-dam and large-reservoir hydropower stations are signifi-cantly affected by complex geological conditions.Traditional prestressed anchor cable reinforcement designs often neglect the uncertainty of soil strength parameters,and the limit equilibrium method struggles to effectively address complex geological environments,resulting in insufficient reliability of the analysis results and low computational efficiency.To address the aforementioned issues,this study innovatively proposed an efficient reliability analysis method integrating active learning support vector machine(AL-SVM)with the strength reduction method.The support vector machine could efficiently approximate the instability criterion of the slope,replacing the traditionally time-consuming strength reduction process to achieve rapid reliability assessment.Additionally,the active learning algorithm it-eratively and actively selected critical sample points near the decision boundary,substantially reducing the computational cost required for training the support vector machine.Taking the reservoir bank slope of the Lianghekou hydropower station as a case study,the proposed method showed an improve-ment in computational efficiency of approximately 98%compared to the traditional Monte Carlo meth-od,while maintaining high accuracy and quantitatively revealing the influence of reinforcement parameter variations on slope failure probability.This method significantly improves the efficiency and accuracy of reliability analysis for the design of slopes reinforced with prestressed anchor cables under complex geological conditions,and provides an innovative solution to the challenges of reliability anal-ysis under complex working conditions.关键词
预应力锚索加固边坡/可靠度/支持向量机/主动学习/两河口水电站Key words
slopes reinforced with prestressed anchor cables/reliability/support vector machine/active learning/Lianghekou hydropower station分类
建筑与水利引用本文复制引用
段祥睿,刘存福,何丰前,谢小创,张洁,陆盟..基于主动学习支持向量机的预应力锚索加固边坡可靠度分析[J].防灾减灾工程学报,2025,45(5):1052-1061,10.基金项目
国家自然科学基金项目(42402280)、国家资助博士后研究人员计划(GZB20240533)、上海市白玉兰人才计划浦江项目(23PJD104)资助 （42402280）
