Selected article for: "machine learning and propose method"

Author: Petrov, K. N.; Gitis, V. G.; Derendyaev, A. B.
Title: A Method of Identification of Potential Earthquake Source Zones
  • Cord-id: 0kkcb724
  • Document date: 2020_8_19
  • ID: 0kkcb724
    Snippet: 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 [Formula: see text] for the Caucasus region. The m
    Document: 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 [Formula: see text] for the Caucasus region. The map of the potential earthquake source zones and a geological interpretation of the decision rule are presented.

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