Statistical properties of complex network for seismicity using depth-incorporated influence radius
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In recent years, seismic time series has been used to construct complex network models in order to describe the seismic complexity. The effect of the factor focal depth has been elided in some of these models. In this paper, we aim to construct a new complex network model for seismicity by considering depth factor from the earthquake catalog and investigate the statistical properties of the network. Since the networks have been proved to be scale-free and small-world properties, the new network models should be studied whether the properties have changed. The results show that the new network model by considering depth factor is still scale-free and small-world. However, it is found that its average degree is smaller than the original network. The clustering coefficient increases at the year including mainshocks. The assortativity coefficient, which demonstrates preferential attachment of nodes, is positive and shows consistent pattern when main shocks occur.
KeywordsComplex network Seismicity Focal depth Assortative mixing
This work has been supported by National Natural Science Foundation of China (NSFC) (Grant Nos. 61806048, 61771121), the Fundamental Research Funds for the Central Universities (Grant No. N171903002), the Open Program of Neusoft Research of Intelligent Healthcare Technology, Co. Ltd. (Grant No. NRIHTOP1802). The authors thank SCSN (Southern California Seismic Network) for providing the seismic data of the study area.
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