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基于经验模态分解识别的全球地震活动性中的微观尺度、中观尺度和宏观尺度及其多重分形特征。

Micro-scale, mid-scale, and macro-scale in global seismicity identified by empirical mode decomposition and their multifractal characteristics.

作者信息

Sarlis Nicholas V, Skordas Efthimios S, Mintzelas Apostolis, Papadopoulou Konstantina A

机构信息

Section of Solid State Physics, Department of Physics, National and Kapodistrian University of Athens, Panepistimiopolis, Zografos, 157 84, Athens, Greece.

Solid Earth Physics Institute, Department of Physics, National and Kapodistrian University of Athens, Panepistimiopolis, Zografos, 157 84, Athens, Greece.

出版信息

Sci Rep. 2018 Jun 15;8(1):9206. doi: 10.1038/s41598-018-27567-y.

Abstract

The magnitude time-series of the global seismicity is analyzed by the empirical mode decomposition giving rise to 14 intrinsic mode functions (IMF) and a trend. Using Hurst analysis one can identify three different sums of these IMFs and the trend which exhibit distinct multifractal behaviour and correspond to micro-, mid- and macro-scales. Their multifractal detrended fluctuation analysis reveals that the micro-scale time-series exhibits anticorrelated behaviour in contrast to the mid-scale one which is long-range correlated. Concerning the mid-scale one, in the range of 30 to 300 consecutive events the maximum entropy method power spectra indicates that it exhibits an 1/f behaviour with α close to 1/3 which is compatible with the long-range correlations identified by detrended fluctuation analysis during periods of stationary seismicity. The results have been also verified to hold regionally for the earthquakes in Japan and shed light on the significance of the mid-scale of 30 to 300 events in the natural time analysis of global (and regional) seismicity. It is shown that when using the mid-scale time-series only, we can obtain results similar to those obtained by the natural time analysis of global seismicity when focusing on the prediction of earthquakes with M ≥ 8.4.

摘要

通过经验模式分解对全球地震活动性的震级时间序列进行分析,得到14个本征模函数(IMF)和一个趋势项。利用赫斯特分析,可以识别出这些IMF和趋势项的三种不同组合,它们表现出不同的多重分形行为,分别对应于微观、中观和宏观尺度。它们的多重分形去趋势波动分析表明,微观尺度时间序列表现出反相关行为,而中观尺度时间序列表现出长程相关。对于中观尺度时间序列,在连续30至300次事件的范围内,最大熵方法功率谱表明它呈现出α接近1/3的1/f行为,这与平稳地震活动期间去趋势波动分析所识别的长程相关性相符。研究结果也已在日本地震的区域范围内得到验证,揭示了30至300次事件的中观尺度在全球(和区域)地震活动性自然时间分析中的重要性。结果表明,仅使用中观尺度时间序列时,在关注M≥8.4级地震预测时,我们可以获得与全球地震活动性自然时间分析相似的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2d98/6003985/12b7c2c5cb81/41598_2018_27567_Fig1_HTML.jpg

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