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A Method of Identification of Potential Earthquake Source Zones

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Computational Science and Its Applications – ICCSA 2020 (ICCSA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12252))

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Abstract

We propose a machine learning method for mapping potential earthquake source zones (ESZ). We use two hypotheses: (1) the recurrence of strong earthquakes and (2) the dependence of sources of strong earthquakes on the properties of the geological environment. To solve this problem, we know the catalog of earthquakes and a set of spatial fields of geological and geophysical features. We tested the method of identification of the potential ESZ with \(m\ge 6.0\) for the Caucasus region. The map of the potential earthquake source zones and a geological interpretation of the decision rule are presented.

The paper is supported by the Russian Science Foundation, project No20-07-00445.

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Authors and Affiliations

  1. The Institute for Information Transmission Problems, Moscow, Russia

    K. N. Petrov, V. G. Gitis & A. B. Derendyaev

Authors
  1. K. N. Petrov
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  2. V. G. Gitis
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  3. A. B. Derendyaev
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Corresponding author

Correspondence to A. B. Derendyaev .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Chair- Center of ICT/ICE, Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Clayton School of Information Technology, Monash University, Clayton, VIC, Australia

    David Taniar

  7. Department of Information Science, Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

  11. Department of Neurology, University of Massachusetts Medical School, Worcester, MA, USA

    Yeliz Karaca

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Petrov, K.N., Gitis, V.G., Derendyaev, A.B. (2020). A Method of Identification of Potential Earthquake Source Zones. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12252. Springer, Cham. https://doi.org/10.1007/978-3-030-58811-3_29

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  • DOI: https://doi.org/10.1007/978-3-030-58811-3_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58810-6

  • Online ISBN: 978-3-030-58811-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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