中国地质灾害与防治学报2023，Vol.34Issue(6)：30-36,7.DOI:10.16031/j.cnki.issn.1003-8035.202303062
基于长短期记忆网络的甘肃舟曲立节北山滑坡变形预测
Deformation prediction of the Northern Mountain landslide in Lijie Town of Zhouqu,Gansu Province based on long-short term memory network
摘要
Abstract
The North Mountain landslide in Lijie Town has been in a long-term creeping deformation state and has experienced multiple landslide and debris flow disasters.Monitoring the surface deformation of landslide to grasp the surface deformation pattern of disaster body is a reliable basis for realizing early warning prediction of geological disaster.In this paper,a machine learning model is introduced to predict the relevant data,and a long and short-term memory network is used to predict the landslide deformation by monitoring the displacement data of North Mountain in Lijie,and the prediction results are compared with the actual data and analyzed.In this paper,root mean square error,mean absolute error,coefficient of determination and explainable variance are used to evaluate the prediction results,among which the coefficient of determination and explainable variance reach 0.99.It shows that the long short-term memory network used in this paper achieves good prediction performance in the prediction of landslide deformation in the North Mountain of Lijie.关键词
滑坡/长短期记忆网络/预测分析/立节北山/机器学习Key words
landslide/LSTM neural network/predictive analysis/North Mountain of Lijie/machine learning分类
天文与地球科学引用本文复制引用
高子雁,李瑞冬,石鹏卿,周小龙,张娟..基于长短期记忆网络的甘肃舟曲立节北山滑坡变形预测[J].中国地质灾害与防治学报,2023,34(6):30-36,7.基金项目
甘肃省自然资源厅科技创新项目(202257) （202257）
甘肃省科技重大专项(19ZD2FA002) （19ZD2FA002）
