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《Water Resources and Power》 2006-06
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Research on Dam Displacement Forecasting Model Based on Least Squares Support Vector Machine

SONG Zhiyu(School of Civil and Hydraulic Eng.,Dalian Univ.of Tech.,Dalian 116023,China) LI Junjie  
Support vector machine(SVM),a machine learning algorithm based on statistical learning theory and its continuation algorithm-Least Squares Support Vector Machine(LSSVM)were presented firstly in this paper,then the LSSVM algorithm was applied to the displacement forecast of concrete dam.According to the measured field data of dam,the authors built the forecasting model of dam displacement based on LSSVM,and the traditional SVM-based forecasting model was built to analyze and compare with LSSVM.The computational results show that both LSSVM algorithm and traditional SVM algorithm have the good feasibility and efficiency,and possess the higher precision forecasting;at the same time,by the results we can also conclude that LSSVM algorithm has the absolute advantage in training efficiency and it is more suitable to solve the modelling problem of large scale data.
【CateGory Index】: TV698.11
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