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Network structure entropy and its dynamical evolution for recurrence networks from earthquake magnitude time series

  • Min Lin
  • Xing Xing Fan
  • Gang Wang
  • Gang Zhao
Regular Article

Abstract

Based on the theory of complex network, we construct a recurrence network for earthquake magnitude time series from California. Network structure entropy and its dynamical evolution of the network is studied. It is found that the network structure entropy of the recurrence network exhibits a peculiar behavior: it stays at a small value before main shock, jumps to a great value at the main shock, and then recovers to normal values gradually. The network structure entropy therefore provides us an approach to characterize main shocks quantitatively.

Keywords

Statistical and Nonlinear Physics 

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Copyright information

© EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.School of Mathematical Sciences, Ocean University of ChinaQingdaoP.R. China
  2. 2.Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and TechnologyQingdaoP.R. China
  3. 3.College of Civil Aviation, NanJing University of Aeronautics and AstronauticsNanjingP.R. China
  4. 4.Faculty of Management Engineering, Huaiyin Institute of TechnologyHuai’anP.R. China

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