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| Titel |
Neural-network-based prediction techniques for single station modeling and regional mapping of the foF2 and M(3000)F2 ionospheric characteristics |
| VerfasserIn |
T. D. Xenos |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 9, no. 5/6 ; Nr. 9, no. 5/6, S.477-486 |
| Datensatznummer |
250006562
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| Publikation (Nr.) |
 copernicus.org/npg-9-477-2002.pdf |
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| Zusammenfassung |
| In this work,
Neural-Network-based single-station hourly daily foF2 and M(3000)F2
modelling of 15 European ionospheric stations is investigated. The data
used are neural networks and hourly daily values from the period 1964-
1988 for training the neural networks and from the period 1989-1994 for
checking the prediction accuracy. Two types of models are presented for
the F2-layer critical frequency prediction and two for the propagation
factor M(3000)F2. The first foF2 model employs the E-layer local
noon calculated daily critical frequency (foE12) and the
local noon F2- layer critical frequency of the previous day. The second foF2
model, which introduces a new regional mapping technique, employs the
Juliusruh neural network model and uses the E-layer local noon calculated
daily critical frequency (foE12), and the previous day
F2-layer critical frequency measured at Juliusruh at noon. The first
M(3000)F2 model employs the E-layer local noon calculated daily critical
frequency (foE12), its ± 3 h deviations and the local
noon cosine of the solar zenith angle (cos c12).
The second model, which introduces a new M(3000)F2 mapping technique,
employs Juliusruh neural network model and uses the E-layer local noon
calculated daily critical frequency (foE12), and the
previous day F2-layer critical frequency measured at Juliusruh at noon. |
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