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      Comparison and Analysis of Network Construction Methods for Seismicity Based on Complex Networks

      1 , 2 , 3 , 4

      Complexity

      Hindawi Limited

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          Abstract

          The approach of the complex network has well described seismic complex systems. In this paper, this is the first time three classical network construction methods for seismicity are compared. By using the same dataset from the Southern California Seismic Network, three networks are constructed. They all present the scale-free, small-world properties, a strength-degree correlation, and an assortative mixing feature. However, they show some differences in the hierarchical clustering feature. On observing the evolution results, three measures show a similar correlation with seismicity dynamics, but one measure shows a different result. These results show that different network construction methods will present some similarities and differences in network properties. This situation needs to be considered, especially when discussing a predictive indicator of seismicity.

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          Most cited references 3

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          Is the sequence of earthquakes in Southern California, with aftershocks removed, Poissonian?

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            An Introduction to Seismology, Earthquakes, and Earth Structure

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                Author and article information

                Contributors
                Journal
                Complexity
                Complexity
                Hindawi Limited
                1099-0526
                1076-2787
                February 1 2021
                February 1 2021
                : 2021
                : 1-11
                Affiliations
                [1 ]College of Medicine & Biological Information Engineering, Northeastern University, Shenyang 110169, China
                [2 ]School of Software, Dalian University of Technology, Dalian 116024, China
                [3 ]Department of Computer and Information Sciences, Northumbria University, Newcastle Upon Tyne NE1 8ST, UK
                [4 ]School of Computer Science & Engineering, Northeastern University, Shenyang 110169, China
                Article
                10.1155/2021/6691880
                © 2021

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