Abstract
The time series of variable geomagnetic field can be considered as nonlinear and nonstationary signal. The view and methods of intelligent signal processing can be used in modeling and forecasting for variable geomagnetic field. This paper proposed a new point of view that Artificial neural network (ANN) with good self-organizing and self-learning could be used for modeling and forecasting variable geomagnetic field and tested this view with four ANN which are RBF, BP, GRNN and ELMAN. Lastly, the results of forecasting were compared and analyzed.
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© 2012 Springer-Verlag GmbH Berlin Heidelberg
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Li, Y., Guan, W., Niu, C., Liu, D. (2012). The Modeling and Forecasting of Variable Geomagnetic Field Based on Artificial Neural Network. In: Jin, D., Lin, S. (eds) Advances in Future Computer and Control Systems. Advances in Intelligent and Soft Computing, vol 159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29387-0_14
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DOI: https://doi.org/10.1007/978-3-642-29387-0_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29386-3
Online ISBN: 978-3-642-29387-0
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