REGRESSION DERIVATIVES AND THEIR APPLICATION IN THE STUDY OF MAGNETIC STORMS

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S. Agayan

Geophysical Center RAS

Email: r.sidorov@gcras.ru
ORCID iD: 0000-0003-3710-1246
SPIN 代码: 7315-6936

Sh. Bogoutdinov

Geophysical Center RAS; Schmidt institute of physics of the Earth of the RAS

Email: r.sidorov@gcras.ru
ORCID iD: 0000-0002-3171-5768
SPIN 代码: 8322-5710

R. Sidorov

Geophysical Center RAS

Email: r.sidorov@gcras.ru
ORCID iD: 0000-0003-2615-4326
SPIN 代码: 9081-7260

An. Soloviev

Geophysical Center RAS; Schmidt institute of physics of the Earth of the RAS

Email: r.sidorov@gcras.ru
ORCID iD: 0000-0002-6476-9471
SPIN 代码: 1506-2412

D. Kamaev

RPA “Typhoon”

Email: r.sidorov@gcras.ru
ORCID iD: 0000-0002-9287-8042
SPIN 代码: 6396-4544

A. Aleksanyan

Obninsk Institute for Nuclear Power Engineering

Email: r.sidorov@gcras.ru

B. Dzeranov

Geophysical Center RAS; Vladikavkaz Scientific Center RAS

编辑信件的主要联系方式.
Email: r.sidorov@gcras.ru
ORCID iD: 0000-0003-3427-0634
SPIN 代码: 2762-2729

参考

  1. Agayan, S., S. Bogoutdinov, A. Soloviev, and R. Sidorov (2016), The Study of Time Series Using the DMA Methods and Geophysical Applications, Data Science Journal, 15, https://doi.org/10.5334/dsj-2016-016.
  2. Agayan, S., S. Bogoutdinov, D. Kamaev, V. Kaftan, M. Osipov, and V. Tatarinov (2021a), Theoretical Framework for Determination of Linear Structures in Multidimensional Geodynamic Data Arrays, Applied Sciences, 11(24), 11,606, https://doi.org/10.3390/app112411606.
  3. Agayan, S., S. Bogoutdinov, R. Krasnoperov, and R. Sidorov (2021b), A Multiscale Approach to Geomagnetic Storm Morphology Analysis Based on DMA Activity Measures, Applied Sciences, 11(24), 12,120, https://doi.org/10.3390/app112412120.
  4. Agayan, S. M., S. R. Bogoutdinov, and R. I. Krasnoperov (2018), Short introduction into DMA, Russian Journal of Earth Sciences, 18(2), 1-10, https://doi.org/10.2205/2018es000618.
  5. Agayan, S. M., A. A. Soloviev, S. R. Bogoutdinov, and Y. I. Nikolova (2019), Regression Derivatives and Their Application to the Study of Geomagnetic Jerks, Geomagnetism and Aeronomy, 59(3), 359-367, https://doi.org/10.1134/s0016793219030022.
  6. Agayan, S. M., V. N. Tatarinov, A. D. Gvishiani, S. R. Bogoutdinov, and I. O. Belov (2020), FDPS algorithm in stability assessment of the Earth’s crust structural tectonic blocks, Russian Journal of Earth Sciences, 20(6), 1-14, https://doi.org/10.2205/2020es000752.
  7. Agayan, S. M., S. R. Bogoutdinov, B. A. Dzeboev, B. V. Dzeranov, D. A. Kamaev, and M. O. Osipov (2022), DPS clustering: New results, Applied Sciences, 12(18), 9335, https://doi.org/10.3390/app12189335.
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  11. Gromova, L. I., N. G. Kleimenova, A. E. Levitin, S. V. Gromov, L. A. Dremukhina, and N. R. Zelinskii (2016), Daytime geomagnetic disturbances at high latitudes during a strong magnetic storm of June 21-23, 2015: The storm initial phase, Geomagnetism and Aeronomy, 56(3), 281-292, https://doi.org/10.1134/s0016793216030051.
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  13. Gvishiani, A. D., R. V. Sidorov, R. Y. Lukianova, and A. A. Soloviev (2016b), Geomagnetic activity during St. Patrick's Day storm inferred from global and local indicators, Russian Journal of Earth Sciences, 16(6), 1-8, https://doi.org/10.2205/2016es000593.
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  16. Kacprzyk, J., A. Wilbik, and S. Zadrożny (2007), Linguistic Summarization of Time Series by Using the Choquet Integral, in Lecture Notes in Computer Science, pp. 284-294, Springer Berlin Heidelberg, https://doi.org/10.1007/978-3-540-72950-1_29.
  17. Kovalev, S. M. (2007), Hybrid fuzzy-temporal models of time series in problems of analysis and identification of weakly formalized processes, in Integrated Models and Soft Computing in Artificial Intelligence. Proceedings of the IVth International Scientific and Practical Conference (Kolomna, May 28-30, 2007), Moscow: Fizmatlit., vol. 1, pp. 26-41.
  18. Lazutin, L. L. (2012), Global and polar magnetic storms, 214 pp., Moscow State University, in Russian.
  19. Mishin, V. M., M. Foerster, T. I. Saifudinova, A. D. Bazarzhapov, Y. A. Karavaev, L. A. Sapronova, and S. I. Solovyev (2007), Spontaneous substorms and ordered type of magnetospheric disturbances during the superstorm of November 20, 2003, Geomagnetism and Aeronomy, 47(4), 429-441, https://doi.org/10.1134/s0016793207040032.
  20. NOAA (2023), National Oceanic and Atmospheric Administartion, https://www.noaa.gov, accesed on 1 November 2023.
  21. OMNI (2023), OMNIWeb Plus, https://omniweb.gsfc.nasa.gov, accesed on 01 November 2023.
  22. Oshchenko, A. A., R. V. Sidorov, A. A. Soloviev, and E. N. Solovieva (2020), Overview of anomality measure application for estimating geomagnetic activity, Geophysical research, 21(4), 51-69, https://doi.org/10.21455/gr2020.4-4.
  23. Pandey, S. K., and S. C. Dubey (2009), Characteristic features of large geomagnetic storms observed during solar cycle 23, Indian Journal of Radio & Space Physics, 38(6), 305-312.
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  25. Soloviev, A., S. Agayan, and S. Bogoutdinov (2017), Estimation of geomagnetic activity using measure of anomalousness, Annals of Geophysics, 59(6), https://doi.org/10.4401/ag-7116.
  26. Soloviev, A., A. Smirnov, A. Gvishiani, J. Karapetyan, and A. Simonyan (2019), Quantification of Sq parameters in 2008 based on geomagnetic observatory data, Advances in Space Research, 64(11), 2305-2320, https://doi.org/10.1016/j.asr.2019.08.038.
  27. Tanaka, H., S. Uejima, and K. Asai (1982), Linear Regression Analysis with Fuzzy Model, IEEE Transactions on Systems, Man, and Cybernetics, 12(6), 903-907, https://doi.org/10.1109/tsmc.1982.4308925.
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