Abstract
The cause-and-effect relations of the dynamics of high-latitude geomagnetic activity (in terms of the AL index) and the type of the magnetic cloud of the solar wind are studied with the use of artificial neural networks. A recurrent neural network model has been created based on the search for the optimal physically coupled input and output parameters characterizing the action of a plasma flux belonging to a certain magnetic cloud type on the magnetosphere. It has been shown that, with IMF components as input parameters of neural networks with allowance for a 90-min prehistory, it is possible to retrieve the AL sequence with an accuracy to ~80%. The successful retrieval of the AL dynamics by the used data indicates the presence of a close nonlinear connection of the AL index with cloud parameters. The created neural network models can be applied with high efficiency to retrieve the AL index, both in periods of isolated magnetospheric substorms and in periods of the interaction between the Earth’s magnetosphere and magnetic clouds of different types. The developed model of AL index retrieval can be used to detect magnetic clouds.
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Barkhatov, N.A. and Revunov, S.E., Iskusstvennye neironnye seti v zadachakh solnechno–zemnoi fiziki (Artificial Neural Networks in Problems of Solar–Terrestrial Physics), Nizhny Novgorod: Povolzh’e, 2010.
Barkhatov, N.A., Korolev, A.V., Ponomarev, S.M., and Sakharov, S.Yu., Long-term forecasting of solar activity indices using neural networks, Radiophys. Quantum Electron., 2001, vol. 44, no. 9, pp. 742–749.
Barkhatov, N.A., Levitin, A.E., and Sakharov, S.Yu., The method of artificial neuron networks as a procedure for reconstructing gaps in records of individual magnetic observatories from the data of other stations, Geomagn. Aeron. (Engl. Transl.), 2002, vol. 42, no. 2, pp. 184–186.
Barkhatov, N.A., Revunov, S.E., and Uryadov, V.P., Forecasting of the critical frequency of the ionosphere F2 layer by the method of artificial neural networks, Int. J. Geomagn. Aeron., 2004, GI2010. doi 10.1029/2004GI000065
Barkhatov, N.A., Vorobjev, V.G., Revunov, S.E., Yagodkina, O.I., and Vinogradov, A.B., Demonstration of the reflection of dynamics of solar wind parameters during the formation of substorm activity using an intelligent tool, in Proc. of the 39th Annual Seminar “Physics of Auroral Phenomena”, Apatity: PGI, 2016, pp. 27–30.
Barkhatov, N.A., Vorobjev, V.G., Revunov, S.E., and Yagodkina, O.I., Effect of solar dynamics parameters on the formation of substorm activity, Geomagn. Aeron. (Engl. Transl.), 2017, vol. 57, no. 3, pp. 251–256.
Henderson, M.G., Reeves, G.D., Belian, R.D., and Murphree, J.,S.D., Observations of magnetospheric substorms occurring with no apparent solar wind/IMF trigger, J. Geophys. Res., 1996, vol. 101, no. A5, pp. 10773–10792. doi 10.1029/96JA00186
Kleimenova, N.G., Kozyreva, O.V, Manninen, J., Raita, T., Kornilova, T.A., and Kornilov, I.A., High-latitude geomagnetic disturbances during the initial phase of a recurrent magnetic storm (from February 27 to March 2, 2008), Geomagn. Aeron. (Engl. Transl.), 2011, vol. 51, no. 6, pp. 730–740.
Lyons, L.R., Substorms: Fundamental observational features, distinction from other disturbances, and external triggering, J. Geophys. Res., 1996, vol. 101, no. A6, pp. 13011–13026. doi 10.1029/95JA01987
Manakova, Yu.V., Pekhteleva, K.A., Barkhatov, N.A., and Revunov, S.E., Spatiotemporal analysis of Pc4-5 disturbances during magnetic storms by the correlation–skeleton method, Vestn. Mininskogo univ., 2016, no. 1, pp. 1–6.
Vorobjev, V.G. and Yagodkina, O.I., Empirical model of auroral precipitation power during substorms, J. Atmos. Sol.-Terr. Phys., 2008, vol. 70, pp. 654–662. doi 10.1016/j.jastp.2007.08.046
Vorobjev, V.G., Yagodkina, O.I., and Zverev, V.L., Investigation of isolated substorms: Generation conditions and characteristics of different phases, Geomagn. Aeron. (Engl. Transl.), 2016, vol. 56, no. 6, pp. 682–693. doi 10.7868/S001679401606016X
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Original Russian Text © N.A. Barkhatov, S.E. Revunov, V.G. Vorobjev, O.I. Yagodkina, 2018, published in Geomagnetizm i Aeronomiya, 2018, Vol. 58, No. 2, pp. 155–162.
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Barkhatov, N.A., Revunov, S.E., Vorobjev, V.G. et al. Studying the Relationship between High-Latitude Geomagnetic Activity and Parameters of Interplanetary Magnetic Clouds with the Use of Artificial Neural Networks. Geomagn. Aeron. 58, 147–153 (2018). https://doi.org/10.1134/S0016793218020020
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DOI: https://doi.org/10.1134/S0016793218020020