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Constructing Weighted Networks of Earthquakes with Multiple-parent Nodes Based on Correlation-Metric

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Complex Networks & Their Applications X (COMPLEX NETWORKS 2021)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1072))

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Abstract

In this paper, we address a problem of constructing weighted networks of earthquakes with multiple parent nodes, where the pairs of earthquakes with strong interaction are connected. To this end, by extending a representative conventional method based on the correlation-metric that produces an unweighted network with a single-parent node, we develop a method for constructing a network with multiple-parent nodes and assigning weight to each link by a link-weighting scheme called logarithmic-inverse-distance. In our experimental evaluation, we use an earthquake catalog that covers the whole of Japan, and select 24 major earthquakes which caused significant damage or casualties in Japan. In comparison to four different link-weighting schema, i.e., uniform, magnitude, inverse-distance, and normalized-inverse-distance, we evaluate the effectiveness of the constructed networks by our proposed method, in terms of the ranking accuracy based on the most basic centrality, i.e., weighted degree measure. As a consequence, we show that our proposed method works well, and then discuss the reasons why weighted networks with multiple-parent nodes can improve the ranking accuracy.

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Notes

  1. 1.

    https://www.data.jma.go.jp/svd/eqev/data/bulletin/hypo.html.

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Acknowledgements

This work was supported by JSPS Grant-in-Aid for Scientific Research (C) (No. 18K11441).

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Authors and Affiliations

  1. Faculty of Informatics, Shizuoka Institute of Science and Technology, Fukuroi, Japan

    Yuki Yamagishi

  2. Center for Advanced Intelligence Project, RIKEN, Kyoto, Japan

    Yuki Yamagishi, Kazumi Saito, Kazuro Hirahara & Naonori Ueda

Authors
  1. Yuki Yamagishi
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  2. Kazumi Saito
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  3. Kazuro Hirahara
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  4. Naonori Ueda
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Corresponding author

Correspondence to Yuki Yamagishi .

Editor information

Editors and Affiliations

  1. Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Madrid, Madrid, Spain

    Rosa Maria Benito

  2. IUT Lumière, University of Lyon, Bron Cedex, France

    Chantal Cherifi

  3. LIB, UFR Sciences et Techniques, University of Burgundy, Dijon, France

    Hocine Cherifi

  4. Grupo Interdisciplinar de Sistemas Complejos, Universidad Carlos III de Madrid, Leganés, Madrid, Spain

    Esteban Moro

  5. Thomas J. Watson College of Engineering and Applied Science, Binghamton University, Binghamton, USA

    Luis M. Rocha

  6. Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona, Tarragona, Spain

    Marta Sales-Pardo

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Yamagishi, Y., Saito, K., Hirahara, K., Ueda, N. (2022). Constructing Weighted Networks of Earthquakes with Multiple-parent Nodes Based on Correlation-Metric. In: Benito, R.M., Cherifi, C., Cherifi, H., Moro, E., Rocha, L.M., Sales-Pardo, M. (eds) Complex Networks & Their Applications X. COMPLEX NETWORKS 2021. Studies in Computational Intelligence, vol 1072. Springer, Cham. https://doi.org/10.1007/978-3-030-93409-5_41

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  • DOI: https://doi.org/10.1007/978-3-030-93409-5_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-93408-8

  • Online ISBN: 978-3-030-93409-5

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