【摘要】 为了研究地震活动的时空复杂性,采用地震活动数据构造了一种加权复杂网络模型,并研究了网络的拓扑和边权结构。结果显示,地震加权网络的节点强度分布及边权分布均具有幂律分布特征,网络的含权团簇系数和平均最近邻度显示地震加权网络具有伴随着边权重-拓扑相关性的分等级的组织结构,团簇熵的计算结果表明,大地震的网络拓扑结构更有序。地震加权网络的动力学演化揭示了在大地震前后一段时期的网络拓扑结构表现出明显的异常。这些结果表明,地震活动显现出一种内在相互作用的网络动力学行为。更多还原

【Abstract】 To study the spatial-temporal complexity of seismicity, we construct weighted complex networks from seismic data and investigate the structural properties of topology and weights of networks. The results show that both strength and weight distributions behave as a power law. The weighted clustering coefficient and the weighted average nearest-neighbors degree show that earthquake networks possess hierarchical organization properties associated with the weights-topology correlations. The entropy of clustering shows the network topology of a larger earthquake is more ordered. The dynamical evolution of weighed earthquake networks reveals the network topology in period before and after a large earthquake shows obvious abnormalities. These results suggest that seismicity shows an network dynamic behavior of the intrinsic interactions.更多还原