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《Seismological Research of Northeast China》 2008-01
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CLASSIFICATION OF THE SEISMIC SERIES TYPE BASED ON THE SUPPORT VECTOR MACHINE

WU An-xu1,JIANG Chang-sheng2,WANG Lin-ying2,LI Ping-an1 LIN Xiang-dong,LU Ya-jun,Mu Kuai-Yong(1.Earthquake Administration of Beijing Municipality,Beijing 100080,China; 2.Institute of Geophysics,China Earthquake Administration,Beijing 100081,China)  
Based on the structural risk minimization principle,algorithm,in artificial intelligence field was introduced in the latest data mining method,support vector machine(SVM) this paper.Classifying models for seismic series type were established according to the linear classify algorithm and the nonlinear classify algorithm of SVM.The best classifying model about seismic series type was gained after trials and analysis,and gotten basically a good coherency between the classifying results and the actual seismic series type.The support vector machine classifying algorithm has an obvious superiority whatever on machine learning or prediction accuracy,and the classifying model for seismic series type based on the SVM theory is feasible,and it can classify the seismic serial type more accurately.
【Fund】: 地震科学联合基金项目(A07058);; 国家科技攻关项目(2006BAC01B02-1-04);; 中国地震局地球物理研究所基本科研业务专项(DQJB06B03)
【CateGory Index】: P315.7
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