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Acta Geophysica

, Volume 67, Issue 6, pp 1515–1523 | Cite as

Statistical properties of complex network for seismicity using depth-incorporated influence radius

  • Xuan HeEmail author
  • Luyang Wang
  • Hongbo Zhu
  • Zheng Liu
Research Article - Solid Earth Sciences
First Online:
  • 39 Downloads

Abstract

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.

Keywords

Complex network Seismicity Focal depth Assortative mixing 
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Notes

Acknowledgements

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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Copyright information

© Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2019

Authors and Affiliations

  1. 1.School of Sino-Dutch Biomedical and Information EngineeringNortheastern UniversityShenyangChina
  2. 2.Neusoft Research of Intelligent Healthcare Technology, Co. Ltd.ShenyangChina
  3. 3.School of Computer Science and EngineeringNortheastern UniversityShenyangChina

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