露天采矿技术2025，Vol.40Issue(2)：36-40,5.DOI:10.13235/j.cnki.ltcm.20240212
基于EMD-LSTM的边坡位移预测模型应用
Application of slope displacement prediction model based on EMD-LSTM
白继元 1肖航 1武志高1
作者信息
- 1. 国能新疆矿业红沙泉二矿有限公司,新疆 昌吉 831100
- 折叠
摘要
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.关键词
位移预测/趋势分解/神经网络/非线性/结合模型Key words
displacement prediction/trend decomposition/neural network/nonlinear/combined model分类
矿业与冶金引用本文复制引用
白继元,肖航,武志高..基于EMD-LSTM的边坡位移预测模型应用[J].露天采矿技术,2025,40(2):36-40,5.
