Recognition of strong earthquake–prone areas with a single learning class

被引：0
|
作者：
A. D. Gvishiani
S. M. Agayan
B. A. Dzeboev
I. O. Belov
机构：
[1] Geophysical Center of the Russian Academy of Sciences,Schmidt Institute of Physics of the Earth
[2] Russian Academy of Sciences,Geophysical Institute, Vladikavkaz Scientific Center
[3] Russian Academy of Sciences,undefined
来源：
Doklady Earth Sciences | 2017年 / 474卷
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摘要：
This article presents a new Barrier recognition algorithm with learning, designed for recognition of earthquake-prone areas. In comparison to the Crust (Kora) algorithm, used by the classical EPA approach, the Barrier algorithm proceeds with learning just on one “pure” high-seismic class. The new algorithm operates in the space of absolute values of the geological–geophysical parameters of the objects. The algorithm is used for recognition of earthquake-prone areas with М ≥ 6.0 in the Caucasus region. Comparative analysis of the Crust and Barrier algorithms justifies their productive coherence.
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页码：546 / 551
页数：5
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