摘要
应用小波变换和最小二乘支持向量机(LSSVM)相结合的方法(小波LSSVM)预测华南地震区年度最大地震。先用小波变换将地震序列分解成不同尺度水平(频率段)的子序列,再用LSSVM方法分别对各子序列建模预测,最后重构各子序列的预测结果并得到最终预测结果。经与周期图方法和LSSVM预测方法比较研究表明:模型输入量中包含地球自转速率变化的小波LSSVM方法预测效果很好,可以用于华南地区年度最大地震预测研究,且地球自转变化与华南地震时间序列的低频部分(趋势)和高频部分(短期变化)之间存在很强的、互不相同的非线性关系。
The models based on wavelet transform（WT） and least squares support vector machine（LS- SVM） was applied to forecast annual the maximum earthquake magnitude in the South China seismic area. Firstly, using wavelet transform the series of annual the maximum earthquake magnitude in the South China seismic area was decomposed into several sub-sequences on different scales （frequency band）. Secondly, the least squares support vector machine was applied to forecast the decomposed sub-sequences, respectively. Finally, the reconstruction of forecasted sub-sequences was used as the final predicted result. The comparison with LS-SVM and period method was made. The forecasted results show that WT and LS-SVM method possesses higher prediction precision and excellent forecasting effect, and prove that the method to combine WT with LS-SVM is feasible to forecast time series of strong earthquakes in the South China seismic area. The forecasted results also suggest that there are the strong and different nonlinear relations between variations of velocity of the Earth＇ s rotation with high frequency portion （trend） and low frequency portion （short variations ） of time sequence of the annual maximum earthquake in the South China seismic area.
出处
《中国地震》
CSCD
北大核心
2006年第2期182-189,共8页
Earthquake Research in China
基金
地震科学联合基金(105086)资助项目
关键词
最小二乘支持向量机
小波变换
华南地震区
地震预测
Least squares support vector machine Wavelet transform South China seismic area Forecasting of strong earthquakes
