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Daily geomagnetic field prediction of INTERMAGNET observatories data using the multilayer perceptron neural network

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Abstract

In this paper, a tentative prediction of daily geomagnetic field and storms is implanted by analyzing the International Real-Time Magnetic Observatory Network data using the artificial neural network (ANN). Solar geomagnetic storms have a big effect on plasma ionospheric disturbance, and our study intend to introduce this effect when predicting ionospheric physical response. The implanted method is based on the prediction of future geomagnetic field components using a multilayer perceptron neural network model. The input is the time, and the output is the X, Y, and Z magnetic field components. Application to geomagnetic data of May 2002 shows that the implanted ANN model can greatly help the geomagnetic storms prediction.

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Acknowledgments

Authors would like to thank the INTERMAGNET network for the free access to Wingst geomagnetic observatory data.

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Authors and Affiliations

  1. LIMOSE, Département de Physique, Faculté des Sciences, Université M’Hamed Bougara de Boumerdès, Avenue de l’indépendance, 35000, Boumerdès, Algeria

    Sid-Ali Ouadfeul & Victor Tourtchine

  2. LABOPHYT, Faculté des Hydrocarbures et de la chimie, Université M’Hamed Bougara de Boumerdès, Avenue de l’indépendance, Boumerdès, Algeria

    Leila Aliouane

Authors
  1. Sid-Ali Ouadfeul
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  2. Victor Tourtchine
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  3. Leila Aliouane
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Correspondence to Sid-Ali Ouadfeul.

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Ouadfeul, SA., Tourtchine, V. & Aliouane, L. Daily geomagnetic field prediction of INTERMAGNET observatories data using the multilayer perceptron neural network. Arab J Geosci 8, 1223–1227 (2015). https://doi.org/10.1007/s12517-014-1308-z

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  • DOI: https://doi.org/10.1007/s12517-014-1308-z

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