Application of slope displacement prediction model based on EMD-LSTM
BAI Jiyuan
XIAO Hang
WU Zhigao
Abstract：In order to improve the accuracy of slope displacement prediction and solve the problems of accuracy and lag in existing methods,a combined model based on empirical mode trend decomposition and long short-term memory neural network is proposed.The predicted model considers displacement changes as the superposition of multiple simple component signals,decomposes displacement relationships into multiple periodic and trend terms through empirical mode decomposition,and then uses long short-term memory neural networks to predict these components separately,ultimately achieving the prediction of nonlinear relationships.The application of example of the slope of an open-pit mine dump show that the prediction accuracy of the model exceeds 90%,which is significantly better than the traditional BP neural network method and can meet the practical needs of engineering.
Keywords：displacement predictiontrend decompositionneural networknonlinearcombined model
Publication Date：2025-04-30
Online Publishing Date：2026-01-31(First online date of this platform, not the publication date of the document)
Pages：5( 36-40 )