On the prediction of solar activity using different neural network models
Item
Title (Dublin Core)
On the prediction of solar activity using different neural network models
Description (Dublin Core)
Accurate prediction of ionospheric parameters is crucial for telecommunication companies. These parameters rely strongly on solar activity. In this paper, we analyze the use of neural networks for sunspot time series prediction. Three types of models are tested and experimental results are reported for a particular sunspot time series: the <i>IR</i>5 index.
Creator (Dublin Core)
Fessant, F.
Bengio, S.
Collobert, D.
Date (Dublin Core)
2018-09-27
Type (Dublin Core)
Text
Format (Dublin Core)
application/pdf
Identifier (Dublin Core)
10.1007/s00585-996-0020-z
https://angeo.copernicus.org/articles/14/20/1996/
Source (Dublin Core)
eISSN: 1432-0576
Language (Dublin Core)
eng
