桂林理工大学学报2016，Vol.36Issue(2)：304-309,6.DOI:10.3969/j.issn.1674-9057.2016.02.018
小波分解层数及分量组合对滑坡预测的影响
Analysis of wavelet decomposition and wavelet component combination for landslide prediction
摘要
Abstract
Based on the characteristics of non-stationary,non-linear and stochastic landslide deformation chan-ges,a combination method of wavelet decomposition and RBF neural network is proposed for the landslide pre-diction.Based on experiments of wavelet decomposition and prediction of the combination of different low fre-quency and high frequency components,the effect of different wavelet decomposition levels,the component combination and predictive steps is analyzed.The experimental results show that only the appropriate decompo-sition level,proper component of combination and predictive step are selected,can we obtain optimal predic-tion.Also,the correctness of the method in the paper is verified.All these studies and results provide reference for the predication of landslide.关键词
滑坡预测/小波分解/分量组合/RBF 神经网络Key words
landslide prediction/wavelet decomposition/wavelet component combination/RBF neural net-work分类
天文与地球科学引用本文复制引用
卢献健,晏红波,梁月吉..小波分解层数及分量组合对滑坡预测的影响[J].桂林理工大学学报,2016,36(2):304-309,6.基金项目
国家自然科学基金项目（41461089）；广西空间信息与测绘重点实验室项目 （）
