Determination of seismic wave velocities on the ground using artificial neural networks
https://doi.org/10.21822/2073-6185-2022-49-2-67-75
Abstract
Objective. The purpose of the study is to determine the velocities of seismic waves on the ground.
Method. To determine the velocities of seismic waves in different parts of the earth's crust, using a sample obtained by mathematical modeling, an artificial neural network was trained. Using at the input of the trained neural network, the real values of the differences in the times of arrival of seismic waves on the ground, we obtain at its output the values of the velocities of seismic waves on the ground.
Result. A method for determining the velocities of seismic waves on the ground using artificial neural networks is proposed. Dependences of the root-mean-square error in determining the velocities of seismic waves on the ground on the training epoch, as well as the distribution of errors in determining the coordinates of the earthquake hypocenter using the obtained information about the structure of the earth, are obtained.
Conclusion. The proposed method makes it possible to determine the structure of the earth's crust more accurately than previously proposed mathematical methods.
About the Authors
Yu. A. Sidorkina
N.E. Bauman Moscow State Technical University (National research University)
Russian Federation
Russian Federation
Dr. Sci. (Eng.), Assoc. Prof., Department Autonomous Information and Control Systems,
5/1 Second Baumanskaya Str., Moscow 105005
T. G. Aslanov
Daghestan State Technical University
Russian Federation
Russian Federation
Cand. Sci. (Eng.), Doctoral Cand., Assoc. Prof., Department of Management and Informatics in Technical
Systems and Computer Engineering,
70 I. Shamilya Ave., Makhachkala 367026
H. D. Magomedov
Daghestan Branch of the Federal Research Center "Unified Geophysical Service" of the Russian Academy of Sciences
Russian Federation
Russian Federation
Director,
16 Belinsky Str., Makhachkala 367008
References
1. Kulchitsky V. E. New hodographs of seismic waves of the Crimean-Black Sea region [Uchenyye zapiski Krymskogo federalʹnogo universiteta imeni V.I. Vernadskogo. Geografiya. Geologiya] Scientific notes of the Crimean Federal University named after V.I. Vernadsky. Geography. Geology. 2018; 4 (70): 164-173 (In Russ)
2. High-speed models. Kola branch of the Unified Geophysical Service of the Russian Academy of Sciences [website]. — URL: http://krsc.ru/?q=ru/Travel_time_models (date of access: 06/21/2022). (In Russ)
3. Shakhramanyan M. A. Technology for assessing the stability and seismic resistance of buildings and structures / M. A. Shakhramanyan, G. M. Nigmetov, M. Yu. Proshlyakov. [Tekhnologii grazhdanskoy bezopasnosti] Civil Security Technologies. 2004; 2 (6): 27-37 (In Russ)
4. Shahramanyan M.A. Seismic risk assessment and earthquake consequences prediction in the tasks of saving the population: (theory and practice) / M.A. Shahramanyan. – 2nd edition, revised and supplemented. Moscow: All-Russian Research Institute for Civil Defense and Emergency Situations of the Ministry of Emergency Situations of Russia, 2000:. 192. ISBN 5-93970- 001-2. (In Russ)
5. Morozov V. N. Forecasting and liquidation of the consequences of accidental explosions and earthquakes: (theory and practice) / V. N. Morozov, M. A. Shakhramanyan. - Moscow: URSS, 1998: 230. (In Russ)
6. Aslanov G.K., Alimerdenov V.S., Aslanov T.G., Tagirov Kh.Yu. Mathematical model for calculating the energy class, intensity and magnitude of an earthquake in real time. [Vestnik Dagestanskogo Gosudarstvennogo Tekhnicheskogo Universiteta. Tekhnicheskiye nauki] Herald of the Daghestan State Technical University. Technical science. 2015;37(2):66-71. https://doi.org/10.21822/2073-6185-2015-37-2-66-71(In Russ)
7. Aslanov G.K., Aslanov T.G., Kurbanmagomedov K.D., Shakhtarin B.I. Investigation of the dependence of errors in determining the coordinates of the earthquake focus on the calculation methods (spheres and hyperboloids). [Vestnik Dagestanskogo Gosudarstvennogo Tekhnicheskogo Universiteta. Tekhnicheskiye nauki] Herald of the Daghestan State Technical University. Technical science. 2017; 44(4):87-98. https://doi.org/10.21822/2073-6185-2017-44-4-87-98 (In Russ)
8. Rogozhin E.A. Earthquake in Iran. Geography. Electronic magazine, 5 [website]. — URL: http://geo.1september.ru/article.php?ID=200400503 (date of access: 04/21/2022). (In Russ)
9. Aslanov G.K., Aslanov T.G., Musaeva U.A. Anomalous errors in determining the coordinates of the source of earthquakes and proposals for their elimination. [Vestnik Dagestanskogo Gosudarstvennogo Tekhnicheskogo Universiteta. Tekhnicheskiye nauki] Herald of the Daghestan State Technical University. Technical Science. 2018; 45(4):78-88. https://doi.org/10.21822/2073-6185-2018-45-4-78-88 (In Russ)
10. Artemiev A.E. Physical foundations of seismic exploration: Textbook - Saratov: OOO Publishing Center "Nauka", 2012: 56. (In Russ)
11. Duchkov A. A. Geometric seismic 1. Ray method: textbook. Novosibirsk: Novosibirsk State Technical University, 2019: 63. - ISBN 978-5-7782-3842-8. Text: electronic. Digital educational resource IPR SMART: [website]. — URL: https://www.iprbookshop.ru/99176.html (date of access: 04/21/2022) (In Russ)
12. Kravtsov Yu.A., Orlov Yu.I. Geometric optics of inhomogeneous media. M.: Nauka, 1980: 306. (In Russ)
13. Goldin S.V. Introduction to geometric seismic: textbook. Novosibirsk: Publishing House of NSU, 2005: 264. (In Russ)
14. Pavlova A. I. Artificial neural networks: textbook.- Moscow: IP Ar Media, 2021: 190 ISBN 978-5-4497-1165-6. — Text: electronic // Digital educational resource IPR SMART: [website]. — URL: https://www.iprbookshop.ru/108228.html (date of access: 06/21/2022). (In Russ)
15. Barsky A. B. Introduction to neural networks: textbook / A. B. Barsky. - 3rd ed. - Moscow, Saratov: Internet University of Information Technologies (INTUIT), IP Ar Media, 2020: 357 - ISBN 978-5-4497-0309-5. — Text: electronic // Digital educational resource IPR SMART: [website]. — URL: https://www.iprbookshop.ru/89426.html (date of access: 06/21/2022). (In Russ)
16. Yakhyaeva G. E. Fuzzy sets and neural networks: textbook / G. E. Yakhyaeva. - 4th ed. — Moscow: Internet University of Information Technologies (INTUIT), IP Ar Media, 202: 315. - ISBN 978-5-4497-0665-2. — Text: electronic. Digital educational resource IPR SMART: [website]. — URL: https://www.iprbookshop.ru/97552.html (date of access: 06/21/2022) (In Russ)
17. Medvedev V. S. Neural networks. MATLAB 6 / V.S. Medvedev, V.G. Potemkin. M.: Dialogue-MEPhI, 2002. (In Russ)
18. Osovsky S. Neural networks for information processing / S. Osovsky; per. from Polish. I.D. Rudinsky. M.: Finance and statistics, 2002. (In Russ)
19. Rutkovsky L. Methods and technologies of artificial intelligence / L. Rutkovsky; per. from Polish. I. D. Rudinsky. - M .: Hot Line - Telecom, 2010. (In Russ)
20. T.G. Aslanov, Yu.A. Sidorkin. Determining the coordinates of the earthquake hypocenter with a known structure of the earth's crust. [Vestnik Dagestanskogo Gosudarstvennogo Tekhnicheskogo Universiteta. Tekhnicheskiye nauki] Herald of the Daghestan State Technical University. Technical Science. 2021; 48(4): 64-71. DOI:10.21822/2073-6185-2021-48-4-64-71(In Russ)
21. T. G. Aslanov, Kh. D. Magomedov, U. A. Musaeva, Kh. Yu. Tagirov. Influence of the spatial arrangement of seismic sensors on the accuracy of determining the earthquake hypocenter. [Vestnik Dagestanskogo Gosudarstvennogo Tekhnicheskogo Universiteta. Tekhnicheskiye nauki] Herald of the Daghestan State Technical University. Technical Science. 2016;43 (4):73-84. DOI:10.21822/2073-6185-2016-43-4-73-84 (In Russ)
Review
For citations:
Sidorkina Yu.A., Aslanov T.G., Magomedov H.D. Determination of seismic wave velocities on the ground using artificial neural networks. Herald of Dagestan State Technical University. Technical Sciences. 2022;49(2):67-75. (In Russ.) https://doi.org/10.21822/2073-6185-2022-49-2-67-75
Views:
299
Email this article 
