Abstract
In this paper, we use the artificial neural network for prediction of ionospheric perturbations by the analysis of the Instrument Plasma Analyzer (IAP) data using the Multilayer Perceptron (MLP) neural network. Data that are used as an input and output for the training of the MLP machine are: the Helium, Electron and Ions densities, Ions temperature, Ions speed and direction. The MLP machine is composed with an input layer, an output layer and a hidden layer. Application to the Demeter satellite data of orbit 27447-1 shows that the MLP neural network machine can give good results for plasma disturbances and can be used for prediction of seismo-ionospheric perturbations.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Bankov, L.G., Parrot, M., Heelis, R.A., Berthelier, -J., Marinov, P.G., Vassileva, A.K.: DEMETER and DMSP satellite observations of the disturbed H+/O+ ratio caused by Earth’s seismic activity in the Sumatra area during December 2004. Advances in Space Research 46(4), 419–430 (2010)
Ouadfeul, S.-A., Aliouane, L.: Lithofacies prediction from well log data using a multi-layer perceptron (MLP) and Kohonen’s self-organizing map (SOM) – a case study from the Algerian Sahara. Pattern Recogn. Phys. 1, 59–62 (2013), doi:10.5194/prp-1-59-2013
Ouadfeul, S.-A., Aliouane, L.: Lithofacies Classification Using the Multilayer Perceptron and the Self-organizing Neural Networks. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds.) ICONIP 2012, Part V. LNCS, vol. 7667, pp. 737–744. Springer, Heidelberg (2012)
Rozhansky, V., Molchanov, P., Veselova, I., Voskoboynikov, Kirk, A., Fishpool, G., Boerner, P., Reiter, D., Coster, D.: Modeling of the edge plasma of MAST Upgrade with a Super-X divertor including drifts and an edge transport barrier. Plasma Phys. Control. Fusion (2013), doi:10.1088/0741-3335/55/3/035005
Svensson, J., von Hellermann, M., König, R.: Analysis of JET charge exchange spectra using neural networks. Plasma Phys. Control. Fusion 41, 315 (1999), doi:10.1088/0741-3335/41/2/016
Taylor, M., Diaz, A.I.: On the deduction of galaxy abundances with evolutionary neural networks. Publications of the Astronomical Society of the Pacific (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ouadfeul, SA., Aliouane, L., Tourtchine, V. (2013). Ionospheric Data Analysis of Demeter Sattelite Using Neural Network: Application to IAP Instrument. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42054-2_64
Download citation
DOI: https://doi.org/10.1007/978-3-642-42054-2_64
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-42053-5
Online ISBN: 978-3-642-42054-2
eBook Packages: Computer ScienceComputer Science (R0)