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


如何引用文章

全文:

开放存取 开放存取
受限制的访问 ##reader.subscriptionAccessGranted##
受限制的访问 订阅存取

详细

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.

作者简介

A. Gvishiani

Geophysical Center of the Russian Academy of Sciences; Schmidt Institute of Physics of the Earth

Email: b.dzeboev@gcras.ru
俄罗斯联邦, Moscow, 119296; Moscow, 123810

S. Agayan

Geophysical Center of the Russian Academy of Sciences

Email: b.dzeboev@gcras.ru
俄罗斯联邦, Moscow, 119296

B. Dzeboev

Geophysical Center of the Russian Academy of Sciences; Geophysical Institute, Vladikavkaz Scientific Center

编辑信件的主要联系方式.
Email: b.dzeboev@gcras.ru
俄罗斯联邦, Moscow, 119296; Vladikavkaz, 362008

I. Belov

Geophysical Center of the Russian Academy of Sciences

Email: b.dzeboev@gcras.ru
俄罗斯联邦, Moscow, 119296

补充文件

附件文件
动作
1. JATS XML

版权所有 © Pleiades Publishing, Ltd., 2017