自动化与仪器仪表2024,Issue(7) :220-224.DOI:10.14016/j.cnki.1001-9227.2024.07.220

基于动态时间规整和改进BP神经网络的滑坡灾害预测系统研究

Research on landslide hazard prediction system based on dynamic time warping and improved BP neural network

陈隆 杨歌 陈汉章
自动化与仪器仪表2024,Issue(7) :220-224.DOI:10.14016/j.cnki.1001-9227.2024.07.220

基于动态时间规整和改进BP神经网络的滑坡灾害预测系统研究

Research on landslide hazard prediction system based on dynamic time warping and improved BP neural network

陈隆 1杨歌 2陈汉章1
扫码查看

作者信息

  • 1. 国能数智科技开发(北京)有限公司,北京 100011
  • 2. 北京龙软科技股份有限公司,北京 100190
  • 折叠

摘要

为了实现对滑坡灾害进行自动化、智能化、实时化的监测和预报,研究以动态时间规整算法和反向传播神经网络为基础,建立了滑坡灾害预测系统自动化控制模型,对滑坡灾害预测系统进行自动化控制的研究.该模型采用改进反向传播神经网络来实现滑坡灾害预测系统的自动控制,实现了滑坡灾害预测系统自动化控制模型的建立.结果表明,数据集测试中百分数误差远远小于工程误差的10%,决定系数都超过了 99%,表明预测值与真实值之间具有很好的相关性,实例验证也说明了该系统的有效性.研究建立的滑坡灾害预测系统自动化控制模型的准确率较高,能够有效地对滑坡灾害进行自动控制,为进一步进行科学有效的研究提供了理论依据和技术支持,具有较好的应用前景.

Abstract

In order to realize the automatic,intelligent and real-time monitoring and forecasting of landslide disaster,the auto-matic control model of landslide disaster prediction system was established based on dynamic time regularization algorithm and back propagation neural network,and the automatic control of landslide disaster prediction system was studied.The model uses the im-proved back propagation neural network to realize the automatic control of the landslide disaster prediction system,and realizes the es-tablishment of the automatic control model of the landslide disaster prediction system.The results show that the percentage error is much less than 10%of the engineering error,and the coefficient of determination is more than 99%,which indicates that there is a good correlation between the predicted value and the real value.The accuracy of the automatic control model of the landslide disaster prediction system is high,which can effectively control the landslide disaster automatically,and provides theoretical basis and techni-cal support for further scientific and effective research,and has a good application prospect.

关键词

动态时间规整/BP神经网络/滑坡灾害预测/自动控制

Key words

dynamic time warping/BP neural network/landslide disaster prediction/automatic control

引用本文复制引用

基金项目

矿山地测管理与地质灾害预警信息系统开发与应用国家能源集团科技创新项目(GJNY-20-220)

出版年

2024
自动化与仪器仪表
重庆工业自动化仪表研究所,重庆市自动化与仪器仪表学会

自动化与仪器仪表

CSTPCD
影响因子:0.327
ISSN:1001-9227
段落导航相关论文