ANN forecast of hourly averaged AE index based on L1 IMF and plasma measurements

Czasopismo : Acta Geophysica
Tytuł artykułu : ANN forecast of hourly averaged AE index based on L1 IMF and plasma measurements

Autorzy :
Lilensten, J.
Laboratoire de Planétologie de Grenoble, OSUG-CNRS, Grenoble, France, jean.lilensten@obs.ujf-grenoble.fr,
Zuccarello, F.
Dipartimento di Fisica e Astronomia, Universitá di Catania, Catania, Italy, fzu@oact.inaf.it,
Zuccarello, F.
Dipartimento di Fisica e Astronomia, Universitá di Catania, Catania, Italy, fzu@oact.inaf.it,
Lundstedt, H.
Swedish Institute of Space Physics, Lund, Sweden, henrik@lund.irf.se,
Kretzschmar, M.
LPCE/CNRS, Orléans, France, matthieu.kretzschmar@cnrs-orleans.fr,
Contarino, L.
INAF Osservatorio Astrofisico di Catania, Catania, Italy, lcont@oact.inaf.it,
Messerotti, M.
INAF-Trieste Astronomical Observatory, Trieste, Italy, messerotti@oats.inaf.it,
Desorgher, L.
Physikalisches Institut, University of Bern, Bern, Switzerland, desorgher@space.unibe.ch,
Usoskin, I. G.
Sodankylä Geophysical Observatory, University of Oulu, Oulu, Finland, Ilya.Usoskin@oulu.fi,
Dudok de Wit, T.
LPCE, CNRS and University of Orléans, Orléans, France, ddwit@cnrs-orleans.fr,
Valtonen, E.
Space Research Laboratory, Department of Physics, University of Turku, Turku, Finland, Eino.Valtonen@utu.fi,
Spurny, F.
Nuclear Physics Institute, Czech Academy of Sciences, Prague, Czech Republic, spurny@ujf.cas.cz,
Daglis, I.
National Observatory of Athens, Institute for Space Applications and Remote Sensing, Athens, Greece, daglis@space.noa.gr,
Romanova, N.
Institute of the Physics of the Earth, Moscow, Russia, runatka@mail.ru,
Milillo, A.
INAF/IFSI, Istituto di Fisica dello Spazio Interplanetario, Roma, Italy, anna.milillo@ifsi-roma.inaf.it,
Amata, E.
Istituto di Fisica dello Spazio Interplanetario, INAF, Roma, Italy, Ermanno.Amata@ifsi-roma.inaf.it,
Abstrakty : The AE index has two components: one driven by the solar wind and one related to the magnetotail unloading process. We recall some past findings on this issue and present a new ANN algorithm for the AE forecasting at 5 and 60 min time scales, built by adding to a previous algorithm a further layer with a hyperbolic tangent transfer function and two more inputs, the output at time t and the difference between the input at time t and the output at time t – 1. We show that, at the 60 min time scale and for AE > 400 nT, the new algorithm performs better than the former one, while no improvement is obtained at the 5 min time scale. This result confirms that the AE component driven by the solar wind can be forecast, at least partially, while the unloading component may not be reproduced from solar wind inputs.

Słowa kluczowe : artificial neural network, storms and substorms, solar wind,
Wydawnictwo : Instytut Geofizyki PAN
Rocznik : 2009
Numer : Vol. 57, no. 1
Strony : 185 – 196
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DOI :
Cytuj : Lilensten, J. ,Zuccarello, F. ,Zuccarello, F. ,Lundstedt, H. ,Kretzschmar, M. ,Contarino, L. ,Messerotti, M. ,Desorgher, L. ,Usoskin, I. G. ,Dudok de Wit, T. ,Valtonen, E. ,Spurny, F. ,Daglis, I. ,Romanova, N. ,Milillo, A. ,Amata, E. , ANN forecast of hourly averaged AE index based on L1 IMF and plasma measurements. Acta Geophysica Vol. 57, no. 1/2009
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