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《Science of Surveying and Mapping》 2011-01
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The research of dam deformation prediction based on PCA-SVM

LV Kai-yun①②,LU Tei-ding②(①China University of Mining,Beijing 100083,China;②East China Institute of Technology,Jiangxi Fuzhou 344000,China)  
Principle component analysis(PCA) can effectively extract data information and eliminate the variables of linear.Support vector machine(SVM) based on statistical learning theory has the significant advantages in modeling process data.The paper apply the principal components analysis in the optimization of dam distortion influence factors.This can solve the influence factor of internal correlation and introducing a factor,reduce the input dimension,simplify the input structure.The data will be simplified as the input factor,reduce the time of SVM learning and improve the efficiency of fitting.The experiment results indicate that this method is of high precision and strong generalization ability.
【Fund】: 江西省自然基金(2009GQS0001);; 武汉大学地球空间环境与大地测量教育部重点实验室开放基金(08-01-04)
【CateGory Index】: TV698.1
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