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《Engineering Journal of Wuhan University》 2017-02
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Time series prediction model of slope displacement based on support vector machines-wavelet nerual network

JIANG Ting;SHEN Zhenzhong;XU Liqun;LIU Chong;TAN Jiacheng;State Key Laboratory of Hydrology-Water Researces and Hydraulic Engineering,Hohai University;College of Water Conservancy and Hydropower Engineering,Hohai University;  
The accurate prediction of rock slope displacement is a difficult problem.In this paper,a new displacement time-series predicted model is proposed by combining the support vector machines and wavelet neural network,named as support vector machines-wavelet neural network.Through studying the measured displacements,parameters optimized by genetic algorithm are used to dynamically forecast the trend of time-series development.Wavelet basis function is applied to analyze the local characteristic of series.By selecting the trend of the bidimensional local series and analyzing absolute error and relative error between measured values and SVM predicting values,the predicting are improved.The model was used to predict displacement time series of strong-unloading slope of the concrete faced rockfill dam.The engineering case study indicates that the model is reliable and accurate;and it can be used for displacement prediction of the rock slopes.
【Fund】: 2016年度江苏省普通高校学术学位研究生科研创新计划项目(编号:KYZZ16_0284);; 江苏省自然科学基金青年基金(编号:BK2012410);; 国家自然科学基金项目(编号:51179062);; 江苏高校优势学科建设工程资助项目;; 中央高校基本业务费项目(编号:2014B11914)
【CateGory Index】: TU433;TP18
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