Neural networks and predictions of solar-terrestrial effects

Details Neural networks and predictions of solar-terrestrial effects Neural networks and predictions of solar-terrestrial effects

Apr 1992

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1992p%26ss...40..457l&link_type=abstract

Planetary and Space Science (ISSN 0032-0633), vol. 40, no. 4, April 1992, p. 457-464.

Computer Science

38

Geomagnetism, Neural Nets, Solar Terrestrial Interactions, Solar Wind, Coronal Holes, Magnetic Storms, Solar Activity

Scientific paper

Neural networks for predictions of solar-terrestrial effects, such as geomagnetic induced currents (GICs), are presented. The following assumptions are made: the geomagnetic activity is mainly controlled by the southward Bz-component of the solar wind. There are three major solar causes of the southward Bz-components, namely the solar sector boundaries (SSB), the coronal mass ejections (CME) and the coronal holes (CH). The mean GIC size has an exponential relation to the geomagnetic activity index Kp. The neural networks were trained with solar input data from various U.S. data bases.

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