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Hernandez et al. 1993
Hernandez, J.V., Tajima, T. and Horton, W. (1993). Neural net forecasting for geomagnetic activity. Geophysical Research Letters 20: doi: 10.1029/93GL02848. issn: 0094-8276.

We use neural nets to construct nonlinear models to forecast the AL index given solar wind and interplanetary magnetic field (IMF) data. We follow two approaches: (1) the state space reconstruction approach, which is a nonlinear generalization of autoregressive-moving average models (ARMA) and (2) the nonlinear filter approach, which reduces to a moving average model (MA) in the linear limit. The database used here is that of Bargatze et al. (1985). ¿ American Geophysical Union 1993

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Abstract

Keywords
Ionosphere, Modeling and forecasting, Magnetospheric Physics, Magnetosphere-ionosphere interactions, Space Plasma Physics, Experimental and mathematical techniques, Space Plasma Physics, Nonlinear phenomena
Journal
Geophysical Research Letters
http://www.agu.org/journals/gl/
Publisher
American Geophysical Union
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