华南地震2024，Vol.44Issue(2)：61-68,8.DOI:10.13512/j.hndz.2024.02.08
基于有限元与LSTM机器学习模型的边坡稳定性预警分析
Early Warning Analysis of Slope Stability Based on Finite Element and LSTM Machine Learning Model
摘要
Abstract
Based on the relationship between precipitation and water content of the slope,the correlation between physical and mechanical properties of the slope and water content was explored.Then,the big data analysis of historical precipitation in a certain area was carried out,and the long short-term memory(LSTM)model was used to predict future precipitation.After that,the finite element strength reduction method was used to analyze and simulate the slope failure and displacement by FLAC3D,and the slope stability coefficient was calculated.The water content of the slope corresponding to the critical stability coefficient was found,and the corresponding precipitation was obtained.According to the prediction,the possible dangerous period was clarified for early warning,so as to facilitate the protection and management of engineering personnel.The results find that the dangerous situation is concentrated in some periods from April to September,which provides a new feasible response method for slope early warning and treatment in the future.关键词
LSTM机器学习模型/有限元模拟/有限差分法/预警治理Key words
LSTM machine learning model/Finite element simulation/Finite difference method/Early warning and management分类
建筑与水利引用本文复制引用
张搏翔,宿凇林,宿文姬,魏平新..基于有限元与LSTM机器学习模型的边坡稳定性预警分析[J].华南地震,2024,44(2):61-68,8.基金项目
广东省自然资源厅科技项目(GDZRZYKJ2024008) （GDZRZYKJ2024008）
国家级大学生创新项目(202410561152)联合资助. （202410561152）
