支持向量机方法在地震短期预测中的应用  

An Application of Support Vector Machine Method to Short-term Earthquake Predication

作　　者：杨柳[1] 

机构地区：[1]天津市地震局,天津300201

出　　处：《华北地震科学》2010年第3期10-15,共6页North China Earthquake Sciences

基　　金：天津市地震局中青年基金课题

摘　　要：支持向量机方法是基于统计学习理论提出的一种机器学习方法,在处理小样本、非线性问题方面有着很强的优势。而地震的孕育发生过程是一个复杂的非线性动力学系统,地震数据时间序列的变化更呈现非线性、不规则等特征。本文系统地分析了天津及其周边地区多种前兆现象,选取反映2至3个月短期情况的前兆测项,使用支持向量机分类方法建立地震综合预测模型,初步结果表明这种方法在地震短期预测中有一定的应用前景。Support Vector Machine（SVM） is a new machine leaning 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 analysis results show that this method is effective and has a good application future.

关 键 词：支持向量机 地震前兆 综合预测 天津 短期 

分 类 号：P315.7[天文地球—地震学]