欢迎访问《地震》，
地震

地震 ›› 2010, Vol. 30 ›› Issue (2): 54-60.

• • 上一篇    下一篇

基于小波分析和最小二乘支持向量机的中国大陆地震震级预测研究

吴芳1,2, 王卫东2, 张永志2, 赵云峰2   

  1. 1.陕西省地震局, 陕西 西安 710068;
    2.长安大学, 陕西 西安 710054
  • 收稿日期:2009-10-09 修回日期:2009-12-25 出版日期:2010-04-30 发布日期:2021-10-18
  • 作者简介:吴芳(1982- ), 女, 山东菏泽人, 2009年获硕士学位, 主要从事地震监测等研究。

Magnitude Forecasting of Earthquake in Mainland China based on Least Squares Support Vector Machine and Wavelet Analysis

WU Fang1,2, WANG Wei-dong2, ZHANG Yong-zhi2, ZHAO Yun-feng2   

  1. 1. Earthquake Administration of Shaanxi Province, Xi'an 710068, China;
    2. Chang'an University, Xi'an 710054, China
  • Received:2009-10-09 Revised:2009-12-25 Online:2010-04-30 Published:2021-10-18

PDF (PC)

摘要： 利用小波分析方法分析百年来中国大陆地震资料, 得到了地震活动在不同时间尺度上的特征, 同时利用各种尺度的小波系数得出地震活动主要周期, 并把此周期值作为参数应用于最小二乘支持向量机预测中。 结果表明, 此方法报准率较高, 平均误差与均方差较小。

关键词: 地震预报, 最小二乘支持向量机, 小波分析, 非线性时间序列

Abstract: Based on the wavelet analysis of earthquake data in Mainland China for the recent century, we determined the characteristics of earthquake activity in different time scales. Meanwhile, the main periods in earthquake activity are obtained from different wavelet coefficients, and as a parameter, the periods are used for earthquake forecasting by means of least square support vector machine (LS-SVM). The results show that this method has a high success rate with smaller average error.

Key words: Earthquake forecast, LS-SVM, Wavelet, Non-linear time series

中图分类号: