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基于EMD-DA-RNN的边坡位移预测

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我国滑坡灾害高发,每年造成了巨大的人员伤亡和经济损失。依托信息技术尤其是物联网技术、人工智能等技术,滑坡的监测预警逐渐自动化、智能化,各种滑坡监测预警系统层出不穷,滑坡监测的数据量、预警的即时性都得到了极大的提升。采用深度学习技术的理论方法,充分利用监测系统获得的数据开展数据挖掘,利用已有的监测数据和各类信息预测滑坡未来一段时间的演化行为,最终实现对滑坡的安全评价。可及时提出滑坡的预防与处置方案,从而保障滑坡影响区域的人类活动。
Slope Displacement Prediction Based on EMD-DA-RNN
The high incidence of landslide disaster has caused a great number of casualties and economic losses every year in China.Relying on information technology especially the Internet technology,modern technologies such as artificial intelligence,automatic and intelligent monitoring and early warning of landslide gradually,all kinds of landslide monitoring and early warning system emerge in endlessly,the volume of landslide monitoring,early warning of immediacy got great ascension,the basis of the method of using deep learning technology theory,Make full use of the data obtained from the monitoring system to carry out data mining,and use the existing monitoring data and various kinds of information to predict the evolution behavior of landslide in the future period of time,and finally realize the safety evaluation of landslide.In this way,the prevention and disposal plan of landslide can be put forward in time,so as to guarantee the human activities in the area affected by landslide.

slopeempirical modal decompositiondual stage attention mechanismrecurrent neural networkdisplacement prediction

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湖南省致力科技有限公司,湖南 长沙 410208

边坡 经验模态分解 双阶段注意力机制 循环神经网络 位移预测

2024

黑龙江交通科技
黑龙江省交通科学研究所,黑龙江省交通科技情报总站

黑龙江交通科技

影响因子:0.977
ISSN:1008-3383
年,卷(期):2024.47(2)
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