土木工程与管理学报2025，Vol.42Issue(1)：20-26,7.DOI:10.13579/j.cnki.2095-0985.2025.20240267
基坑地墙渗漏指标预测及风险等级评价方法
Prediction of Leakage Index and Evaluation of Leakage Risk for Foundation Pit Wall
摘要
Abstract
Clean energy sources such as solar and wind power require the use of limited surface space,while human's development and utilization of underground space indirectly promote the growth of clean energy.This paper focuses on the issue of foundation pit wall leakage in excavation accidents.Using the finite element software ABAQUS,1000 different leakage scenarios were simulated,and data on three physical quantities—pore water pressure in observation wells,lateral displacement of founda-tion pit walls,and ground settlement were extracted over a 7-day period in these environments.After dimensionality reduction using principal component analysis(PCA),the data were used to construct four types of neural network models:artificial neural network(ANN),recurrent neural network(RNN),long short-rerm memory(LSTM),and gated recurrent unit(GRU).These models were em-ployed to predict key variables of excavation leakage and assess the risk levels of these variables.The paper also explores the use of decision tree and random forest for predicting leakage risk levels.Com-paring the regression and classification approaches for risk assessment,the classification method quickly predicts the leakage levels,while the regression method predicts the key variables of leakage.关键词
基坑渗漏/安全预警/机器学习/神经网络/主成分分析Key words
foundation pit leakage/safety warning/machine learning/neural network/principal component analysis分类
交通工程引用本文复制引用
张迪,孙峰,叶晓剑,曹刚,邱子琪,曹子君,洪义,王立忠,王立林..基坑地墙渗漏指标预测及风险等级评价方法[J].土木工程与管理学报,2025,42(1):20-26,7.基金项目
国家自然科学基金(52238008 （）
52122906) （）
