| Support vector machine method for forecasting future strong earthquakes in Chinese mainland |
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| 引用本文： | 王炜 刘悦 李国正 吴耿锋 马钦忠 赵利飞 林命週. Support vector machine method for forecasting future strong earthquakes in Chinese mainland[J]. 地震学报(英文版), 2006, 19(1): 30-38. DOI: 10.1007/s11589-001-0030-6 |
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| 作者姓名： | 王炜 刘悦 李国正 吴耿锋 马钦忠 赵利飞 林命週 |
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| 作者单位： | [1]Earthquake Administration of Shanghai Municipality, Shanghai 200062, China [2]School of Computer Engineering and Science, Shanghai University, Shanghai 200072, China |
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| 基金项目： | Joint Seismological Science Foundation of China （104090） |
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| 摘 要： | Statistical learning theory is for small-sample statistics. And support vector machine is a new machine learning method based on the statistical learning theory. The support vector machine not only has solved certain problems in many learning methods, such as small sample, over fitting, high dimension and local minimum, but also has a higher generalization （forecasting） ability than that of artificial neural networks. The strong earthquakes in Chinese mainland are related to a certain extent to the intensive seismicity along the main plate boundaries in the world, however, the relation is nonlinear. In the paper, we have studied this unclear relation by the support vector machine method for the purpose of forecasting strong earthquakes in Chinese mainland.
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| 文章编号： | 1000-9116（2006）01-0030-09 |
| 收稿时间： | 2005-05-08 |
| 修稿时间： | 2005-10-24 |
Support vector machine method for forecasting future strong earthquakes in Chinese mainland |
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| WANG Wei,LIU Yue,LI Guo-zheng,WU Geng-feng,MA Qin-zhong,ZHAO Li-fei,LIN Ming-zhou. Support vector machine method for forecasting future strong earthquakes in Chinese mainland[J]. Acta Seismologica Sinica(English Edition), 2006, 19(1): 30-38. DOI: 10.1007/s11589-001-0030-6 |
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| Authors: | WANG Wei LIU Yue LI Guo-zheng WU Geng-feng MA Qin-zhong ZHAO Li-fei LIN Ming-zhou |
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| Affiliation: | 1. Earthquake Administration of Shanghai Municipality, Shanghai 200062, China
2. School of Computer Engineering and Science, Shanghai University, Shanghai 200072, China |
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| Abstract: | Statistical learning theory is for small-sample statistics. And support vector machine is a new machine learning method based on the statistical learning theory. The support vector machine not only has solved certain problems in many learning methods, such as small sample, over fitting, high dimension and local minimum, but also has a higher generalization (forecasting) ability than that of artificial neural networks. The strong earthquakes in Chinese mainland are related to a certain extent to the intensive seismicity along the main plate boundaries in the world,however, the relation is nonlinear. In the paper, we have studied this unclear relation by the support vector machine method for the purpose of forecasting strong earthquakes in Chinese mainland. |
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| Keywords: | statistical learning theory support vector machine artificial neural networks earthquake situa tion |
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