工程地质学报2016，Vol.24Issue(5)：721-731,11.DOI:10.13544/j.cnki.jeg.2016.05.001
WA联合ELM与OS-ELM的滑坡位移预测模型
PREDICTIVE MODELING OF LANDSLIDE DISPLACEMENT BY WAVELET ANALYSIS AND MULTIPLE EXTREME LEARNING MACHINES
摘要
Abstract
The curve landslide cumulative displacement is usually nonlinear.Hence,it is challenging to build predictive models with less error.In this paper,we propose a new methodology of embedding wavelet analysis with basic extreme learning machine(ELM)and online sequential extreme learning machine(OS-ELM)to predict the cumulative displacement.Firstly,by wavelet transformation,the cumulative function of displacement is discretized into periodic displacement and trend displacement.Secondly,basic ELM and OS-ELM are selected to predict the periodic displacement and trend displacement.Lastly,the cumulative displacement function is computed by ensembling the predicted periodic and trend displacement values.For basic ELM,a sigmoid function is selected as the kernel function and a single hidden layer with 33 nodes performs best.For OS-ELM,the prediction error reaches its minimum with 1 00 hidden nodes when the RBF function is selected as the kernel function.RMSE for ELM is 0.1 423 and for OS-ELMis 0.1 31 5.This methodology with high predictive accuracy performs better in comparison with other methods.关键词
滑坡累积位移/非线性特性/位移预测/小波函数/ELM/OS-ELMKey words
Landslide cumulative displacement/Nonlinear curve/Displacement prediction/Wavelet analysis/ELM/OS-ELM分类
天文与地球科学引用本文复制引用
李骅锦,许强,何雨森,魏勇..WA联合ELM与OS-ELM的滑坡位移预测模型[J].工程地质学报,2016,24(5):721-731,11.基金项目
国家重点基础研究发展计划（973）项目（2013CB733200），国家创新研究群体科学基金（41521002）资助． （）
