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A Neural Network Model for the Critical Frequency of the F2 Ionospheric Layer over Cyprus

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Book cover Engineering Applications of Neural Networks (EANN 2009)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 43))

Abstract

This paper presents the application of Neural Networks for the prediction of the critical frequency foF2 of the ionospheric F2 layer over Cyprus. This ionospheric characteristic (foF2) constitutes the most important parameter in HF (High Frequency) communications since it is used to derive the optimum operating frequency in HF links. The model is based on ionosonde measurements obtained over a period of 10 years. The developed model successfully captures the variability of the foF2 parameter.

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References

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Author information

Authors and Affiliations

  1. Computer Science and Engineering Department, Frederick University, 7 Y. Frederickou St., Palouriotisa, Nicosia, 1036, Cyprus

    Haris Haralambous & Harris Papadopoulos

Authors
  1. Haris Haralambous
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  2. Harris Papadopoulos
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Editor information

Editors and Affiliations

  1. Faculty of Computing, London Metropolitan University, 166-220 Holloway Road, N7 8DB, London, UK

    Dominic Palmer-Brown

  2. School of Computing, IT and Engineering, University of East London, Docklands Campus, 4-6 University Way, E16 2RD, London, UK

    Chrisina Draganova  & Haris Mouratidis  & 

  3. School of Computing, IT and Engineering, University of East London, London, UK

    Elias Pimenidis

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© 2009 Springer-Verlag Berlin Heidelberg

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Haralambous, H., Papadopoulos, H. (2009). A Neural Network Model for the Critical Frequency of the F2 Ionospheric Layer over Cyprus. In: Palmer-Brown, D., Draganova, C., Pimenidis, E., Mouratidis, H. (eds) Engineering Applications of Neural Networks. EANN 2009. Communications in Computer and Information Science, vol 43. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03969-0_34

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  • DOI: https://doi.org/10.1007/978-3-642-03969-0_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03968-3

  • Online ISBN: 978-3-642-03969-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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