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| Titel |
The development of a regional geomagnetic daily variation model using neural networks |
| VerfasserIn |
P. R. Sutcliffe |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
0992-7689
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| Digitales Dokument |
URL |
| Erschienen |
In: Annales Geophysicae ; 18, no. 1 ; Nr. 18, no. 1, S.120-128 |
| Datensatznummer |
250013888
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| Publikation (Nr.) |
 copernicus.org/angeo-18-120-2000.pdf |
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| Zusammenfassung |
Global and regional geomagnetic field models
give the components of the geomagnetic field as functions of position and epoch;
most utilise a polynomial or Fourier series to map the input variables to the
geomagnetic field values. The only temporal variation generally catered for in
these models is the long term secular variation. However, there is an increasing
need amongst certain users for models able to provide shorter term temporal
variations, such as the geomagnetic daily variation. In this study, for the
first time, artificial neural networks (ANNs) are utilised to develop a
geomagnetic daily variation model. The model developed is for the southern
African region; however, the method used could be applied to any other region or
even globally. Besides local time and latitude, input variables considered in
the daily variation model are season, sunspot number, and degree of geomagnetic
activity. The ANN modelling of the geomagnetic daily variation is found to give
results very similar to those obtained by the synthesis of harmonic coefficients
which have been computed by the more traditional harmonic analysis of the daily
variation.
Key words. Geomagnetism and paleomagnetism (time
variations; diurnal to secular) · Ionosphere (modelling and forecasting) |
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