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volume 11 issue 17 pages 7972

System-Analytical Method of Earthquake-Prone Areas Recognition

Publication typeJournal Article
Publication date2021-08-28
scimago Q2
wos Q2
SJR0.521
CiteScore5.5
Impact factor2.5
ISSN20763417
Computer Science Applications
Process Chemistry and Technology
General Materials Science
Instrumentation
General Engineering
Fluid Flow and Transfer Processes
Abstract

Typically, strong earthquakes do not occur over the entire territory of the seismically active region. Recognition of areas where they may occur is a critical step in seismic hazard assessment studies. For half a century, the Earthquake-Prone Areas (EPA) approach, developed by the famous Soviet academicians I.M. Gelfand and V.I. Keilis-Borok, was used to recognize areas prone to strong earthquakes. For the modern development of ideas that form the basis of the EPA method, new mathematical methods of pattern recognition are proposed. They were developed by the authors to overcome the difficulties that arise today when using the EPA approach in its classic version. So, firstly, a scheme for the recognition of high seismicity disjunctive nodes and the vicinities of axis intersections of the morphostructural lineaments was created with only one high seismicity learning class. Secondly, the system-analytical method FCAZ (Formalized Clustering and Zoning) has been developed. It uses the epicenters of fairly weak earthquakes as recognition objects. This makes it possible to develop the recognition result of areas prone to strong earthquakes after the appearance of epicenters of new weak earthquakes and, thereby, to repeatedly correct the results over time. It is shown that the creation of the FCAZ method for the first time made it possible to consider the classical problem of earthquake-prone areas recognition from the point of view of advanced systems analysis. The new mathematical recognition methods proposed in the article have made it possible to successfully identify earthquake-prone areas on the continents of North and South America, Eurasia, and in the subduction zones of the Pacific Rim.

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GOST |
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GOST Copy
Dzeboev B. A. et al. System-Analytical Method of Earthquake-Prone Areas Recognition // Applied Sciences (Switzerland). 2021. Vol. 11. No. 17. p. 7972.
GOST all authors (up to 50) Copy
Dzeboev B. A., Gvishiani A. D., Agayan S. M., Belov I. O., Karapetyan J., Dzeranov B. V., Barykina Y. V. System-Analytical Method of Earthquake-Prone Areas Recognition // Applied Sciences (Switzerland). 2021. Vol. 11. No. 17. p. 7972.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.3390/app11177972
UR - https://doi.org/10.3390/app11177972
TI - System-Analytical Method of Earthquake-Prone Areas Recognition
T2 - Applied Sciences (Switzerland)
AU - Dzeboev, Boris A.
AU - Gvishiani, Alexei D.
AU - Agayan, Sergey M.
AU - Belov, Ivan O.
AU - Karapetyan, Jon
AU - Dzeranov, Boris V.
AU - Barykina, Yuliya V
PY - 2021
DA - 2021/08/28
PB - MDPI
SP - 7972
IS - 17
VL - 11
SN - 2076-3417
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2021_Dzeboev,
author = {Boris A. Dzeboev and Alexei D. Gvishiani and Sergey M. Agayan and Ivan O. Belov and Jon Karapetyan and Boris V. Dzeranov and Yuliya V Barykina},
title = {System-Analytical Method of Earthquake-Prone Areas Recognition},
journal = {Applied Sciences (Switzerland)},
year = {2021},
volume = {11},
publisher = {MDPI},
month = {aug},
url = {https://doi.org/10.3390/app11177972},
number = {17},
pages = {7972},
doi = {10.3390/app11177972}
}
MLA
Cite this
MLA Copy
Dzeboev, Boris A., et al. “System-Analytical Method of Earthquake-Prone Areas Recognition.” Applied Sciences (Switzerland), vol. 11, no. 17, Aug. 2021, p. 7972. https://doi.org/10.3390/app11177972.