岩土力学2017，Vol.38Issue(12)：3660-3669,10.DOI:10.16285/j.rsm.2017.12.034
基于集合经验模态分解与支持向量机回归的位移预测方法:以三峡库区滑坡为例
Displacement prediction method based on ensemble empirical mode decomposition and support vector machine regression-a case of landslides in Three Gorges Reservoir area
摘要
Abstract
Many landslides in Three Gorges Reservoir area are featured by stepwise increasing surface displacement along the time.Responding composition model is one of the main methods for displacement prediction of landslides.Currently,high-frequency and low-frequency components of inducing factors are usually ignored.A method based on reconstruction of time series by ensemble empirical mode decomposition (EEMD) and particle swarm optimization based support vector machine regression (PSO-SVR) prediction for displacement is proposed.The typical Baishuihe landslide in Three Gorges Reservoir is taken as an example.Firstly,the monitored surface displacement time series from July 2003 to March 2013 is decomposed into trend and fluctuant components by EEMD.The trend component can be predicted using quadratic polynomial equation fitted by the least square method.With EEMD and t-test methods,rainfalls and reservoir levels time series are reconstructed into high-frequency rainfalls,low-frequency rainfalls,high-frequency reservoir levels and low-frequency reservoir levels,respectively.Combined with other common factors,high-frequency rainfalls and monthly variations of reservoir levels are selected as predominant factors for fluctuant displacement components by method of gray relational analysis (GRA).Finally,PSO-SVR is utilized for prediction purpose.Application results show that average relative error is 0.009 8,variance ratio is 0.023 9 and small error probability is 1,which demonstrate preferable effect of the proposed method.For verification and testing,5 other typical landslides in Three Gorges Reservoir area are presented to test the effectiveness of our method,which can provide references for similar landslides.关键词
三峡库区/滑坡位移预测/诱发因素/集合经验模态分解/PSO-SVRKey words
Three Gorges Reservoir/landslide displacement prediction/inducing factors/ensemble EMD/PSO-SVR分类
建筑与水利引用本文复制引用
邓冬梅,梁烨,王亮清,王昌硕,孙自豪,王聪,董曼曼..基于集合经验模态分解与支持向量机回归的位移预测方法:以三峡库区滑坡为例[J].岩土力学,2017,38(12):3660-3669,10.基金项目
国家自然科学基金项目(No.41372310) （No.41372310）
中国地质大学(武汉)中央高校基本科研业务费专项资金资助项目(No.1610491T07).This work was supported by the National Natural Science Foundation of China (41372310) and the Fundamental Research Funds for National University,China University of Geosciences (Wuhan) (1610491T07). （武汉）
