Jon Karapetyan

Prof. Jon Karapetyan

Director
orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 August 2020 in Earth-Science Reviews
Verified
Journal Article
Closed access
AIAlik Ismail-Zadeh
Alik Ismail-Zadeh
SAShota Adamia
Shota Adamia
ACAleksandre Chabukiani
Aleksandre Chabukiani
TCTamaz Chelidze
Tamaz Chelidze
SCSierd Cloetingh
Sierd Cloetingh
ASAlexander Soloviev
Alexander Soloviev

28 August 2021 in Applied Sciences
Verified
Journal Article
Open access
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Boris DzeboevBoris Dzeboev
Boris Dzeboev
Alexei GvishianiAlexei Gvishiani
Alexei Gvishiani
SASergey Agayan
Sergey Agayan
IBIvan Belov
Ivan Belov
Jon KarapetyanJon Karapetyan
Jon Karapetyan
YBYuliya V. Barykina
Yuliya V. Barykina
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.

15 December 2018 in Vestnik Otdeleniya nauk o Zemle RAN
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Journal Article
Closed access
AGA. D.I Gvishiani
A. D.I Gvishiani
ASA. A. Soloviev
A. A. Soloviev
Roman SidorovRoman Sidorov
Roman Sidorov
RKR. I. Krasnoperov
R. I. Krasnoperov
AGA. A. Grudnev
A. A. Grudnev
ASA. O. Simonyan
A. O. Simonyan

10 April 2020 in Russian Journal of Earth Sciences
Verified
Journal Article
Closed access
Jon KarapetyanJon Karapetyan
Jon Karapetyan
RSR. S. Sargsyan
R. S. Sargsyan
KKK. S. Kazaryan
K. S. Kazaryan
BDB. V. Dzeranov
B. V. Dzeranov
BDB. A. Dzeboev
B. A. Dzeboev
RKR.~K. Karapetyan
R.~K. Karapetyan

1 December 2019 in Advances In Space Research
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Journal Article
Closed access
ASAnatoly Soloviev
Anatoly Soloviev
ASArtem Smirnov
Artem Smirnov
AGAlexei Gvishiani
Alexei Gvishiani
Jon KarapetyanJon Karapetyan
Jon Karapetyan
ASAnahit Simonyan
Anahit Simonyan

5 December 2019 in Russian Journal of Earth Sciences
Verified
Journal Article
Closed access
BDBoris Dzeranov
Boris Dzeranov
ASA. A. Soloviev
A. A. Soloviev
BDB. V. Dzeranov
B. V. Dzeranov
Jon KarapetyanJon Karapetyan
Jon Karapetyan
NSN. A. Sergeeva
N. A. Sergeeva