基于k-核解析的地震活动网络特征分析
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摘要
根据地震活动表现出的网络动力学行为和地震系统所具有的时空复杂性,从复杂网络的角度分析地震活动.采用基于时空影响域的地震网络构造方法,对地震网络进行k-核解析.实验结果表明,对地震网络进行k-核解析得到的最高核的节点彼此聚集在一起.通过分析最高核节点与大地震的位置关系,发现大地震发生的地点与最高核节点所在的位置相邻.在一些大地震发生前,地震网络的最高核数会迅速增加,在大地震发生时最高核数达到最大值,大地震发生后最高核数又恢复到稳定状态.地震网络的k-核解析为我们分析地震系统和研究地震的发生规律提供了一种新的途径.
According to the dynamical behavior of seismic activity and the spatiotemporal complexity of seismic system,this paper analyzed the seismic activities from the perspective of complex network.Using the solution based on spacetime influence domain to construct earthquake network,a method of k-core decomposition was applied to the earthquake networks.The experiment result shows that the nodes in the highest layer cluster together.An important phenomenon is found that the strong quakes tend to occur at the location where the nodes in the highest layer are by analyzing their location information.What is more,the value of the highest layer will rapidly increase before a strong quake,then it will reach the maximum when a strong quake occurs,finally it will return to a stable state.k-core decomposition of earthquake networks will provide a new way for us to analyze and research the seismological system.
According to the dynamical behavior of seismic activity and the spatiotemporal complexity of seismic system,this paper analyzed the seismic activities from the perspective of complex network.Using the solution based on spacetime influence domain to construct earthquake network,a method of k-core decomposition was applied to the earthquake networks.The experiment result shows that the nodes in the highest layer cluster together.An important phenomenon is found that the strong quakes tend to occur at the location where the nodes in the highest layer are by analyzing their location information.What is more,the value of the highest layer will rapidly increase before a strong quake,then it will reach the maximum when a strong quake occurs,finally it will return to a stable state.k-core decomposition of earthquake networks will provide a new way for us to analyze and research the seismological system.
引文
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Ferreira D S R,Papa A R R,Menezes R.2014.Towards evidences of long-range correlations in seismic activity[J].arXiv Preprint arXiv:1405.0307.
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Gkantsidis C,Mihail M,Zegura E.2003.Spectral analysis of internet topologies[C]∥Twenty-Second Annual Joint Conference of the IEEE Computer and Communications.San Francisco,CA:IEEE:364--374.
Hauksson E,Jones L M,Hutton K,Eberhart-Phillips D.1993.The 1992Landers earthquake sequence:Seismologicalobservations[J].J Geophys Res,98(B11):19835--19858.
He X,Zhao H,Cai W,Liu Z,Si S Z.2014.Earthquake networks based on space-time influence domain[J].Physica A,407:175--184.
uczak T.1991.Size and connectivity of the k-core of a random graph[J].Discr Mathemat,91(1):61--68.
Seidman S B.1983.Network structure and minimum degree[J].Soc Networks,5(3):269--287.
Southern California Earthquake Data Center.2014.Earthquake catalogs[EB/OL].[2014-04-12].http:∥service.scedc.caltech.edu/eq-catalogs/date_mag_loc.php.
Taborda R,Bielak J.2001.Large-scale earthquake simulation:Computational seismology and complex engineering systems[J].Comp Sci Eng,13(4):14--27.
谢周敏.2011.地震活动的网络拓扑结构和网络动力学行为[J].震灾防御技术,6(1):1--17.Xie Z M.2011.Network topology and network dynamical behavior of seismicity[J].Technology for Earthquake Disaster Prevention,6(1):1--17(in Chinese).
徐道一.2001.大地震发生的网络性质:兼论有关地震预测的争论[J].地学前缘,8(2):211--216.Xu D Y.2001.The network features of large earthquake occurrence and some words on the debate of earthquake prediction[J].Earth Science Frontiers,8(2):211--216(in Chinese).
周涛,柏文洁,汪秉宏,刘之景,严钢.2005.复杂网络研究概述[J].物理,34(1):31--36.Zhou T,Bai W J,Wang B H,Liu Z J,Yan G.2005.A brief review of complex networks[J].Physics,34(1):31--36(in Chinese).
Abe S,Suzuki N.2004.Scale-free network of earthquakes[J].Euro Phys Lett,65(4):581.
Baiesi M,Paczuski M.2005.Complex networks of earthquakes and aftershocks[J].Nonlin Process Geophys,12(1):1--11.
Bottiglieri M,de Arcangelis L,Godano C,Lippiello E.2010.Multiple-time scaling and universal behavior of the earthquake interevent time distribution[J].Phys Rev Lett,104(15):158501.
Dorogovtsev S N,Goltsev A V,Mendes J F F.2006.k-core organization of complex networks[J].Phys Rev Lett,96:040601.
Ferreira D S R,Papa A R R,Menezes R.2014.Towards evidences of long-range correlations in seismic activity[J].arXiv Preprint arXiv:1405.0307.
Gaertler M,Patrignani M.2004.Dynamic analysis of the autonomous system graph[C/OL]∥International Workshop onInter-domain Performance and Simulation.[2014-04-12].http:∥patrignani.dia.uniroma3.it/papers/files/ASGraphDynamicAnalysis.pdf.
Gardner J K,Knopoff L.1974.Is the sequence of earthquakes in southern California,with aftershocks removed,Poissonian[J].Bull Seismol Soc Am,64(5):1363--1367.
Gkantsidis C,Mihail M,Zegura E.2003.Spectral analysis of internet topologies[C]∥Twenty-Second Annual Joint Conference of the IEEE Computer and Communications.San Francisco,CA:IEEE:364--374.
Hauksson E,Jones L M,Hutton K,Eberhart-Phillips D.1993.The 1992Landers earthquake sequence:Seismologicalobservations[J].J Geophys Res,98(B11):19835--19858.
He X,Zhao H,Cai W,Liu Z,Si S Z.2014.Earthquake networks based on space-time influence domain[J].Physica A,407:175--184.
uczak T.1991.Size and connectivity of the k-core of a random graph[J].Discr Mathemat,91(1):61--68.
Seidman S B.1983.Network structure and minimum degree[J].Soc Networks,5(3):269--287.
Southern California Earthquake Data Center.2014.Earthquake catalogs[EB/OL].[2014-04-12].http:∥service.scedc.caltech.edu/eq-catalogs/date_mag_loc.php.
Taborda R,Bielak J.2001.Large-scale earthquake simulation:Computational seismology and complex engineering systems[J].Comp Sci Eng,13(4):14--27.
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