Strong earthquake-prone areas recognition based on the algorithm with a single pure training class. II. Caucasus, {\itshape {M}} $ \geq $ 6.0. Variable EPA method
Journal: Rossijskij žurnal nauk o zemle/Russian journal of earth sciences
Year: 2019

Strong earthquake-prone areas recognition ( 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