Data-Driven Combination-Interval Prediction for Landslide Displacement Based on Copula and VMD-WOA-KELM Method  

作　　者：Longqi Li Yunhuang Yang Tianzhi Zhou Mengyun Wang 

机构地区：[1]State Key Laboratory of Geological Hazard Prevent and Geo Environmental Protection,Chengdu University of Technology,Chengdu 610059,China

出　　处：《Journal of Earth Science》2025年第1期291-306,共16页地球科学学刊(英文版)

基　　金：financially supported by the National Natural Science Foundation of China(Nos.42277149,41502299,41372306);the Research Planning of Sichuan Education Department,China(No.16ZB0105);the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project(Nos.SKLGP2016Z007,SKLGP2018Z017,SKLGP2020Z009);Chengdu University of Technology Young and Middle Aged Backbone Program(No.KYGG201720);Sichuan Provincial Science and Technology Department Program(No.19YYJC2087);China Scholarship Council。

摘　　要：To tackle the difficulties of the point prediction in quantifying the reliability of landslide displacement prediction,a data-driven combination-interval prediction method(CIPM)based on copula and variational-mode-decomposition associated with kernel-based-extreme-learningmachine optimized by the whale optimization algorithm(VMD-WOA-KELM)is proposed in this paper.Firstly,the displacement is decomposed by VMD to three IMF components and a residual component of different fluctuation characteristics.The key impact factors of each IMF component are selected according to Copula model,and the corresponding WOA-KELM is established to conduct point prediction.Subsequently,the parametric method(PM)and non-parametric method(NPM)are used to estimate the prediction error probability density distribution(PDF)of each component,whose prediction interval(PI)under the 95%confidence level is also obtained.By means of the differential evolution algorithm(DE),a weighted combination model based on the PIs is built to construct the combination-interval(CI).Finally,the CIs of each component are added to generate the total PI.A comparative case study shows that the CIPM performs better in constructing landslide displacement PI with high performance.

关 键 词：landslide displacement interval prediction combination method COPULA LANDSLIDES VMD-WOA-KELM 

分 类 号：P642.22[天文地球—工程地质学]