STRONG EARTHQUAKE-PRONE AREAS RECOGNITION BASED ON THE ALGORITHM WITH A SINGLE PURE TRAINING CLASS. II. CAUCASUS, M $ \geq $ 6.0. VARIABLE EPA METHOD - Dzeboev B.A.; Soloviev A.A.; Dzeranov B.V.; Karapetyan J.K.; Sergeeva N.A. (Федеральное государственное бюджетное учреждение науки Геофизический центр Российской академии наук, 2019)
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.
Keywords: EARTHQUAKE-PRONE AREAS RECOGNITION; EPA; CORA-3; BARRIER-3; CAUCASUS; SEISMIC HAZARD ASSESSMENT; FUZZY SET