Articles | Volume 12, issue 1
https://doi.org/10.1007/s00585-994-0019-2
© European Geosciences Union 1994
https://doi.org/10.1007/s00585-994-0019-2
© European Geosciences Union 1994
31 Jan 1994
31 Jan 1994
Prediction of geomagnetic storms from solar wind data with the use of a neural network
H. Lundstedt
P. Wintoft
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- A neural network approach to the classification of electron and proton whistlers X. Miniere et al. 10.1016/0021-9169(95)00077-1
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