Performance of IRI-based ionospheric critical frequency calculations with reference to forecasting

Basit Öğe Kaydı
dc.authoridÜNAL, İbrahim/0000-0001-8497-4459
dc.authorwosidÜNAL, İbrahim/ABH-5657-2020
dc.contributor.authorUnal, Ibrahim
dc.contributor.authorSenalp, Erdem Turker
dc.contributor.authorYesil, Ali
dc.contributor.authorTulunay, Ersin
dc.contributor.authorTulunay, Yurdanur
dc.date.accessioned2024-08-04T20:32:42Z
dc.date.available2024-08-04T20:32:42Z
dc.date.issued2011
dc.departmentİnönü Üniversitesien_US
dc.description.abstractIonospheric critical frequency (foF2) is an important ionospheric parameter in telecommunication. Ionospheric processes are highly nonlinear and time varying. Thus, mathematical modeling based on physical principles is extremely difficult if not impossible. The authors forecast foF2 values by using neural networks and, in parallel, they calculate foF2 values based on the IRI model. The foF2 values were forecast 1 h in advance by using the Middle East Technical University Neural Network model (METU-NN) and the work was reported previously. Since then, the METU-NN has been improved. In this paper, 1 h in advance forecast foF2 values and the calculated foF2 values have been compared with the observed values considering the Slough (51.5 degrees N, 0.6 degrees W), Uppsala (59.8 degrees N, 17.6 degrees E), and Rome (41.8 degrees N, 12.5 degrees E) station foF2 data. The authors have considered the models alternative to each other. The performance results of the models are promising. The METU-NN foF2 forecast errors are smaller than the calculated foF2 errors. The models may be used in parallel employing the METU-NN as the primary source for the foF2 forecasting.en_US
dc.description.sponsorshipEU [296]en_US
dc.description.sponsorshipThis work is partially supported by the EU Action of the COST 296 (Mitigation of Ionospheric Effects on Radio Systems).en_US
dc.identifier.doi10.1029/2010RS004428
dc.identifier.issn0048-6604
dc.identifier.issn1944-799X
dc.identifier.scopus2-s2.0-79551622104en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1029/2010RS004428
dc.identifier.urihttps://hdl.handle.net/11616/95249
dc.identifier.volume46en_US
dc.identifier.wosWOS:000286768200001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherAmer Geophysical Unionen_US
dc.relation.ispartofRadio Scienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectNeural-Network Techniqueen_US
dc.subjectModelen_US
dc.subjectFof2en_US
dc.titlePerformance of IRI-based ionospheric critical frequency calculations with reference to forecastingen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu