Comparison of the Efficiency of Machine Learning Methods in Studying the Importance of Input Features in the Problem of Forecasting the Dst Geomagnetic Index-Reference-Cited by-同舟云学术

Comparison of the Efficiency of Machine Learning Methods in Studying the Importance of Input Features in the Problem of Forecasting the Dst Geomagnetic Index

Published:2023-04 Issue:2 Volume:63 Page:161-171
ISSN:0016-7932
Container-title:Geomagnetism and Aeronomy
language:en
Short-container-title:Geomagn. Aeron.

Author:

Vladimirov R. D.,Shirokiy V. R.,Myagkova I. N.,Barinov O. G.,Dolenko S. A.

Publisher

Pleiades Publishing Ltd

Subject

Space and Planetary Science,Geophysics

Link

https://link.springer.com/content/pdf/10.1134/S0016793222600795.pdf

Reference31 articles.

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3. Barkhatov, N.A., Bellustin, N.S., Levitin. A.E., and Sakharov, S.Y., Comparison of efficiency of artificial neural networks for forecasting the geomagnetic activity index Dst, Radiophys. Quantum Electron., 2000, vol. 43, no. 5, pp. 347–355.

4. Belov, A.V., Villoresi, J., Dorman, L.I., et al., Effect of the space on operation of satellites, Geomagn. Aeron. (Engl. Transl.), 2004, vol. 44, no. 4, pp. 461–468.

5. Artificial neural networks for determining magnetospheric conditions;J. Bortnik,2018

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