辽宁工程技术大学学报（自然科学版）2025，Vol.44Issue(2)：186-193,8.DOI:10.11956/j.issn.1008-0562.20240110
组合机器学习模型基坑沉降变形预测方法研究
Research on foundation pit settlement deformation prediction method based on combined machine learning model
摘要
Abstract
Foundation pit excavation will cause the surrounding soil to settle,and may even cause disasters such as cracks in adjacent buildings or underground pipelines,so it is of great significance to predict the deformation of foundation pit in advance for the safety of foundation pit engineering.In order to achieve high-precision prediction of foundation pit surface settlement,this paper utilized convolutional neural network(CNN),BP(back-propagation)neural network and long short term memory(LSTM)neural network algorithms to construct a foundation pit settlement deformation prediction model.Based on the entropy method and the CRITIC weight method,three machine learning algorithms were combined to establish a combinatorial prediction model.Based on the foundation pit deformation monitoring data,the accuracy of the single prediction model and the combined prediction model used in this paper was evaluated.The results show that compared with the prediction model of a single machine learning algorithm,the average absolute error of the combined entropy method prediction model is reduced by 90.79％,the mean square error by 99.44％,and the average absolute percentage error by 90.33％.The average absolute error of the combined prediction model of the CRITIC method was reduced by 86.40％,the mean square error was reduced by 98.31％,and the average absolute percentage error was reduced by 84.94％.The combined prediction model proposed in this paper has better prediction performance than that of the single model,and the research is of great significance to improve the prediction accuracy of foundation pit surface settlement and ensure the safety of foundation pit construction.关键词
基坑/组合预测/机器学习/熵值法/CRITIC法Key words
foundation pit/fusion prediction/machine learning/entropy method/CRITIC method分类
土木建筑引用本文复制引用
马雪利,姚华彦,朱勇超,汪明武,成潇博,朱艺媛..组合机器学习模型基坑沉降变形预测方法研究[J].辽宁工程技术大学学报（自然科学版）,2025,44(2):186-193,8.基金项目
国家自然科学基金项目(42104019) （42104019）
长三角科技创新共同体联合攻关课题(2022CSJGG1205) （2022CSJGG1205）
