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dc.contributor.authorElmunim, N A-
dc.contributor.authorAbdullah, M-
dc.contributor.authorHasbi, A M-
dc.contributor.authorBahari, S A-
dc.date.accessioned2015-04-09T11:31:09Z-
dc.date.available2015-04-09T11:31:09Z-
dc.date.issued2015-03-
dc.identifier.issn0975-105X (Online); 0367-8393 (Print)-
dc.identifier.urihttp://hdl.handle.net/123456789/31324-
dc.description28-34en_US
dc.description.abstractThe ionosphere is a notable source of error that disrupts the accuracy of the global position system (GPS) signal to the ground by changing the speed and direction of the signal propagation and in the process causing a delay in the signal. Therefore, forecasting the ionospheric delay is very important to reduce the GPS positioning error. In this work, statistical Holt-Winter method was chosen due to its suitability in forecasting time series with repeated seasonal patterns. This involved the forecast of ionospheric delays during the period October 2009 - December 2010 using GPS Ionospheric Scintillation and TEC Monitor (GISTM) over Universiti Kebangsaan Malaysia (UKM) station, at geographic coordinates 2.55°N, 101.46°E. The comparison of Additive and Multiplicative Holt-Winter models was done in terms of month-to-month error measurement, the difference of the actual and forecasting delay and the monthly average of the forecast. The maximum difference between actual and forecasting delay was estimated to be about 2 m. The results showed that the accuracy of the Multiplicative model in forecasting the ionospheric delay is better by 2% than that of Additive model going by its small error values and higher accuracy. en_US
dc.language.isoen_USen_US
dc.publisherNISCAIR-CSIR, Indiaen_US
dc.relation.ispartof94.20.Cf; 91.10.Fc; 95.75.Wxen_US
dc.rights CC Attribution-Noncommercial-No Derivative Works 2.5 Indiaen_US
dc.sourceIJRSP Vol.44(1) [March 2015]en_US
dc.subjectIonospheric delayen_US
dc.subjectTotal electron contenten_US
dc.subjectHolt-Winter Additive modelen_US
dc.subjectHolt-Winter Multiplicative modelen_US
dc.titleComparison of statistical Holt-Winter models for forecasting the ionospheric delay using GPS observationsen_US
dc.typeArticleen_US
Appears in Collections:IJRSP Vol.44(1) [March 2015]

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