【摘要】 将小波变换和支持向量机用于中国大陆年度最大地震震级预测。先用小波变换把中国大陆年度最大地震序列分解成几个不同尺度水平(频率)的子序列,然后使用支持向量机对分解后的子序列分别进行预测,最后通过重构几个子序列的支持向量机预测结果得到最终预测结果,预测次年中国大陆最大地震震级。与支持向量机和神经网络方法对比,结果表明小波变换和支持向量机相结合方法具有更高的预测精度,预测效果很好,说明此方法可用于地震时间序列预测。更多还原

【Abstract】 In this paper,the model based on wavelet transform and support vector machine(SVM) was applied to forecast the annual maximum earthquake magnitude in China’s mainland.Firstly,using wavelet transform the series of the annual maximum earthquake sequence in china’s mainland was decomposed into several sub-sequences with different scales(frequency band).Secondly,the 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,to forecast the maximum earthquake magnitude in China’s mainland next year.The comparison of SVM with ANN method was made.The forecasted results show that our method possesses higher prediction precision and excellent forecasting effect,and prove that the method to combine wavelet transform with SVM is feasible to forecast time series of strong earthquakes.更多还原