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《Engineering Journal of Wuhan University》 2007-01
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Research on safety monitoring forecasting model for dam based on chaos optimization support vector machine algorithm

SONG Zhiyu,LI Junjie(School of Civil and Hydraulic Engineering,Dalian Univ.of Technology,Dalian 116023,China)  
Support vector machine(SVM),a machine learning algorithm based on statistical learning theory is presented firstly.Aiming at the blindness of man made choice of the parameter and kernel function of SVM,a chaos optimization method is applied to select parameters of SVM;and a novel algorithm,chaos optimization support vector machine(COSVM) is put forward.According to the measured field data(1997-2004) of the Fengman Dam,the COSVM-based safety monitoring model is applied to forecast the deformation of the dam.Compared with statistical regression model and BP neural network model,a conclusion is drawn that the COSVM-based model possesses not only higher precision of forecasting,but also better generalization ability in long-interval forecasting.
【CateGory Index】: TV698.1
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