Russian Journal of Earth Sciences Russian Journal of Earth Sciences Russian Journal of Earth Sciences 1681-1208 46495 10.2205/2019ES000691 ОРИГИНАЛЬНЫЕ СТАТЬИ ORIGINAL ARTICLES ОРИГИНАЛЬНЫЕ СТАТЬИ Strong earthquake-prone areas recognition based on the algorithm with a single pure training class. II. Caucasus, M ≥ 6.0. Variable EPA method Strong earthquake-prone areas recognition based on the algorithm with a single pure training class. II. Caucasus, M ≥ 6.0. Variable EPA method Dzeboev B A Dzeboev B A b.dzeboev@gcras.ru Soloviev A A Soloviev A A Dzeranov B V Dzeranov B V Karapetyan J K Karapetyan J K Sergeeva N A Sergeeva N A Geophysical Institute, Affiliate of Vladikavkaz Science Center RAS ru Geophysical Institute, Affiliate of Vladikavkaz Science Center RAS ru Institute of Earthquake Prediction Theory and Mathematical Geophysics RAS ru Institute of Earthquake Prediction Theory and Mathematical Geophysics RAS ru Geophysical Institute, Affiliate of Vladikavkaz Science Center RAS ru Geophysical Institute, Affiliate of Vladikavkaz Science Center RAS ru Institute of Geophysics and Engineering Seismology after A. Nazarov ru Institute of Geophysics and Engineering Seismology after A. Nazarov ru Geophysical Center RAS ru Geophysical Center RAS ru 19 6 29 10 2021 https://rjes.ru/en/nauka/article/46495/view

Strong earthquake-prone areas recognition (M ≥ 6.0) in the Caucasus is performed by means of the new "Barrier-3" pattern recognition algorithm. The obtained result is compared with potentially high seismicity zones recognized previously using the "Cora-3" pattern recognition algorithm. It is proposed to define an interpretation of the integral recognition result by the "Barrier-3" and "Cora-3" algorithms as a fuzzy set of recognition objects in the vicinity of which strong earthquakes may occur in the Caucasus.

Strong earthquake-prone areas recognition (M ≥ 6.0) in the Caucasus is performed by means of the new "Barrier-3" pattern recognition algorithm. The obtained result is compared with potentially high seismicity zones recognized previously using the "Cora-3" pattern recognition algorithm. It is proposed to define an interpretation of the integral recognition result by the "Barrier-3" and "Cora-3" algorithms as a fuzzy set of recognition objects in the vicinity of which strong earthquakes may occur in the Caucasus.

 Earthquake-prone areas recognition EPA Cora-3 Barrier-3 Caucasus seismic hazard assessment fuzzy set Earthquake-prone areas recognition EPA Cora-3 Barrier-3 Caucasus seismic hazard assessment fuzzy set This work was conducted in the framework of budgetary funding of the Geophysical Center of RAS, the Institute of Earthquake Prediction Theory and Mathematical Geophysics of RAS and the Geophysical Institute VSC RAS, adopted by the Ministry of Science and Higher Education of the Russian Federation.

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