基于小波神经网络的某边坡预测研究  

Study on Slope Deformation Forecast Based On Wavelet Analysis

作　　者：黄永红[1] 徐勇 

机构地区：[1]重庆市勘测院,重庆江北400020 [2]重庆市合川区规划局,重庆合川401520

出　　处：《四川理工学院学报（自然科学版）》2011年第3期370-372,共3页Journal of Sichuan University of Science & Engineering(Natural Science Edition)

摘　　要：边坡的地表位移监测是滑坡安全监控中的重要内容,对监测资料进行及时、合理和有效的分析,获取滑坡变形规律和安全状况是滑坡监测的重要工作之一。文章将基于BP算法的小波神经网络预测模型引入变形监测预报中,对工程实例进行了预测。结果表明小波神经网络预测可以取得良好的效果,且自适应预测能力较强。The surface deformation monitoring of slope is an important content of the safety monitoring of slope,it is one of the important tasks to make timely,reasonable and effective analysis for slope observation data for getting the surface deformation regularities and the safety states of slope.The wavelet network is used in setting up the deformation forecasting model.The results show that the wavelet neural network can get better results,and it has better adaptive predictive ability.

关 键 词：边坡 监测 小波神经网络 预测 

分 类 号：TU433[建筑科学—岩土工程]