An Application of Support Vector Machine Method to Short-Term Earthquake Predication
详细信息
- 责任者：Yang Liu (Earthquake Administration of Tianjin ; Tianjin 300201 ; China)
- 刊名：North China Earthquake Sciences
- 出版年：2010
- 卷期：28(3)
- 关键词：支持向量机 ; support vector machine ; 地震预测 ; earthquake prediction ; 天津 ; Tianjin
- 页码：p.10-15
- 图表：illus., 4 tables, 11 refs.
- 分类号：0500
- issnNo：ISSN1003-1375
- isbnNo：CN13-1102/P
摘要
Support Vector Machine (SVM) is a new machine learning method based on statistical learning theory. This method has obvious advantages in processing small-sample and nonlinear problems. As a matter of fact, the generation of earthquake is a very complicated nonlinear dynamic problem and the earthquake data manifest the nonlinear and irregular characteristics. This paper analyzed the seismic precursor of Tianjin City and neighborhood systematically and presented a synthetic earthquake predication model with a method of SVM classification by employing the seismic precursor information which reflects the short-term situation of 2～3 months. The results show that the method is effective and has a good application future.