STRONG EARTHQUAKE-PRONE AREAS RECOGNITION BASED ON THE ALGORITHM WITH A SINGLE PURE TRAINING CLASS. II. CAUCASUS, M $ \geq $ 6.0. VARIABLE EPA METHOD

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dc.contributor.authorDzeboev B.A.
dc.contributor.authorSoloviev A.A.
dc.contributor.authorDzeranov B.V.
dc.contributor.authorKarapetyan J.K.
dc.contributor.authorSergeeva N.A.
dc.date.accessioned2020-08-21T06:28:50Z
dc.date.available2020-08-21T06:28:50Z
dc.date.issued2019
dc.description.abstractStrong 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.
dc.identifierhttps://cyberleninka.ru/article/n/strong-earthquake-prone-areas-recognition-based-on-the-algorithm-with-a-single-pure-training-class-ii-caucasus-m-geq-6-0-variable-epa-method
dc.identifierФедеральное государственное бюджетное учреждение науки Геофизический центр Российской академии наук
dc.identifier.citationRussian Journal of Earth Sciences, 2019, 19, 6
dc.identifier.urihttps://repository.geologyscience.ru/handle/123456789/17566
dc.publisherФедеральное государственное бюджетное учреждение науки Геофизический центр Российской академии наук
dc.subjectEARTHQUAKE-PRONE AREAS RECOGNITION
dc.subjectEPA
dc.subjectCORA-3
dc.subjectBARRIER-3
dc.subjectCAUCASUS
dc.subjectSEISMIC HAZARD ASSESSMENT
dc.subjectFUZZY SET
dc.titleSTRONG EARTHQUAKE-PRONE AREAS RECOGNITION BASED ON THE ALGORITHM WITH A SINGLE PURE TRAINING CLASS. II. CAUCASUS, M $ \geq $ 6.0. VARIABLE EPA METHOD
dc.typetext
dc.typeArticle

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