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Earthquake networks based on space–time influence domain

Author

Listed:
  • He, Xuan
  • Zhao, Hai
  • Cai, Wei
  • Liu, Zheng
  • Si, Shuai-Zong

Abstract

A new construction method of earthquake networks based on the theory of complex networks is presented in this paper. We propose a space–time influence domain for each earthquake to quantify the subsequence of earthquakes which are directly influenced by the former earthquake. The size of the domain is according to the magnitude of earthquake. In this way, the seismic data in the region of California are mapped to a topology of earthquake network. It is discovered that the earthquake networks in different time spans behave as scale-free networks. This result can be interpreted in terms of the Gutenberg–Richter law. Discovery of small-world characteristic is also reported on the earthquake network constructed by our method. The Omori law emerges as a feature of seismicity for the out-going links of the network. These characteristics highlight a novel aspect of seismicity as a complex phenomenon and will help us to reveal the internal mechanism of seismic system.

Suggested Citation

  • He, Xuan & Zhao, Hai & Cai, Wei & Liu, Zheng & Si, Shuai-Zong, 2014. "Earthquake networks based on space–time influence domain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 175-184.
    • Handle: RePEc:eee:phsmap:v:407:y:2014:i:c:p:175-184
    DOI: 10.1016/j.physa.2014.03.093
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    References listed on IDEAS

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    1. Li, Hui & Zhao, Hai & Cai, Wei & Xu, Jiu-Qiang & Ai, Jun, 2013. "A modular attachment mechanism for software network evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2025-2037.
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    5. Abe, Sumiyoshi & Suzuki, Norikazu, 2004. "Small-world structure of earthquake network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 337(1), pages 357-362.
    6. Abe, Sumiyoshi & Pastén, Denisse & Suzuki, Norikazu, 2011. "Finite data-size scaling of clustering in earthquake networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(7), pages 1343-1349.
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    Cited by:

    1. Zhang, Ya & Zhao, Hai & He, Xuan & Pei, Fan-Dong & Li, Guang-Guang, 2016. "Bayesian prediction of earthquake network based on space–time influence domain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 138-149.
    2. Wang, Jin-Fa & He, Xuan & Si, Shuai-Zong & Zhao, Hai & Zheng, Chunyang & Yu, Hao, 2019. "Using complex network theory for temporal locality in network traffic flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 722-736.
    3. He, Xuan & Zhao, Hai & Cai, Wei & Li, Guang-Guang & Pei, Fan-Dong, 2015. "Analyzing the structure of earthquake network by k-core decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 34-43.

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