STRONG EARTHQUAKE-PRONE AREAS RECOGNITION BASED ON THE ALGORITHM WITH A SINGLE PURE TRAINING CLASS. II. CAUCASUS, M ≥ 6.0. VARIABLE EPA METHOD
Abstract and keywords
Abstract (English):
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
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References

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