Development of the Algorithmic Basis of the FCAZ Method for Earthquake-Prone Area Recognition

Author:

Agayan Sergey M.1,Dzeboev Boris A.1ORCID,Bogoutdinov Shamil R.12,Belov Ivan O.1,Dzeranov Boris V.1ORCID,Kamaev Dmitriy A.3

Affiliation:

1. Geophysical Center of the Russian Academy of Sciences, 119296 Moscow, Russia

2. Schmidt Institute of Physics of the Earth of the Russian Academy of Sciences, 123995 Moscow, Russia

3. Research and Production Association “Typhoon”, 249038 Obninsk, Russia

Abstract

The present paper continues the series of publications by the authors devoted to solving the problem of recognition regions with potential high seismicity. It is aimed at the development of the mathematical apparatus and the algorithmic base of the FCAZ method, designed for effective recognition of earthquake-prone areas. A detailed description of both the mathematical algorithms included in the FCAZ in its original form and those developed in this paper is given. Using California as an example, it is shown that a significantly developed algorithmic FCAZ base makes it possible to increase the reliability and accuracy of FCAZ recognition. In particular, a number of small zones located at a fairly small distance from each other but having a close “internal” connection are being connected into single large, high-seismicity areas.

Funder

Ministry of Science and Higher Education of the Russian Federation

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference61 articles.

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3. Atkinson, G.M. (2012, January 24–28). The Integration of Emerging Trends in Engineering Seismology. Proceedings of the 13th World Conference on Earthquake Engineering, Lisbon, Portugal.

4. Kijko, A. (2011). Encyclopedia of Solid Earth Geophysics, Springer.

5. How to combine deterministic and probabilistic methods for assessing earthquake hazards;Krinitzsky;Eng. Geol.,2003

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