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《Earthquake》 2005-04
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The support vector machine method for time sequence forecasting of strong earthquakes in China′s mainland

WANG Wei~1,LIU Yue~2,LI Guo-zheng~2,WU Geng-feng~2LIN Ming-zhou~1,MA Qin-zhong~1,ZHAO Li-fei~1(1.Earthquake Administration!of Shanghai Municipality,Shanghai 200062;2.School of Computer Engineering and Science,Shanghai University,Shanghai 200072,China)  
Statistical learning theory is a small-sample statistics theory.Support vector machine is a new machine learning method based on statistical learning theory.It is not only helpful to solve some problems,such as small-sample,devilishly learning,big-dimension and local minimum,but also is of strong generalization(forecasting) ability.The support vector machine was used to predict the time sequence of the strong earthquakes,and to forecast the maximum earthquake magnitude in China's mainland next year.The results show the method has good forecasting effect.The results also indicate that the activity of strong earthquakes in the world and the sunspot.Though the relation is still not clear,nonlinear relation is well shown by use of the support vector machine.
【Fund】: 地震科学联合基金项目(104090)
【CateGory Index】: P315.7;
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