Strong-Earthquake-Prone Areas Recognition Based on an Algorithm with a Single Pure Training Class: I. Altai–Sayan–Baikal Region, М ≥ 6.0


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Abstract

A new version of the Barrier algorithm is proposed for recognition of strong-earthquake prone regions based on training over a single reliable training class. The modification of the algorithm consists in creating blocks that reveal the geological–geophysical features (attributes) characteristic of the recognized highly seismic objects and provide their quantitative estimates. The recognition of the areas prone to earthquakes with M ≥ 6.0 is carried out for the Altai–Sayan–Baikal region. The results of the recognition are used for assessing the effect of the remote earthquakes that occurred in the Altai–Sayan orogenic region on the stability of structural-tectonic crustal blocks in the contact zone of the West Siberian platform and the Siberian plate.

About the authors

B. A. Dzeboev

Geophysical Center, Russian Academy of Sciences; Geophysical Institute, Vladikavkaz Scientific Center, Russian Academy of Sciences

Author for correspondence.
Email: b.dzeboev@gcras.ru
Russian Federation, Moscow, 119296; Vladikavkaz, 362002

A. D. Gvishiani

Geophysical Center, Russian Academy of Sciences; Schmidt Institute of Physics of the Earth, Russian Academy of Sciences

Email: b.dzeboev@gcras.ru
Russian Federation, Moscow, 119296; Moscow, 123242

I. O. Belov

Geophysical Center, Russian Academy of Sciences

Email: b.dzeboev@gcras.ru
Russian Federation, Moscow, 119296

S. M. Agayan

Geophysical Center, Russian Academy of Sciences

Email: b.dzeboev@gcras.ru
Russian Federation, Moscow, 119296

V. N. Tatarinov

Geophysical Center, Russian Academy of Sciences; Schmidt Institute of Physics of the Earth, Russian Academy of Sciences

Email: b.dzeboev@gcras.ru
Russian Federation, Moscow, 119296; Moscow, 123242

Yu. V. Barykina

Geophysical Center, Russian Academy of Sciences

Email: b.dzeboev@gcras.ru
Russian Federation, Moscow, 119296

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