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Total electron content prediction model using the artificial neural networks over the Eastern Africa Region

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dc.creator Sulungu, Emmanuel D.
dc.creator Uiso, Christian BS
dc.date 2020-11-25T08:34:58Z
dc.date 2020-11-25T08:34:58Z
dc.date 2019
dc.date.accessioned 2021-05-06T13:00:48Z
dc.date.available 2021-05-06T13:00:48Z
dc.identifier Sulungu, E. D., & Uiso, C. (2019). Total electron content prediction model using the artificial neural networks over the Eastern Africa Region. Tanzania Journal of Science, 45(3), 502-517.
dc.identifier 0856-1761
dc.identifier http://hdl.handle.net/20.500.12661/2626
dc.identifier.uri http://hdl.handle.net/20.500.12661/2626
dc.description Abstract. Full text article is available at https://www.ajol.info/index.php/tjs/article/view/191958
dc.description In this paper, development of a model using NN technique for prediction of GPS TEC over the Eastern Africa region is presented. TEC data was obtained from the Africa array and IGS network of ground based dual-frequency GPS receivers from 18 stations within the East African region. It covers approximately the area from ~2.6°N to ~26.9°S in magnetic latitudes and from ~95°E to ~112oE in magnetic longitudes. The input layer of the developed model consisted of seven neurons which were selected by considering the parameters that are known to affect the TECv data. The results showed that when the number of hidden layer neurons surpassed about 18, the RMSEs were noted to continuously increase indicating poor predictions beyond this number. The RMSE at this point was observed to be about 5.2 TECU which was lowest of all. The errors and relative errors were fairly small. Developed NN model estimated GPS TECv very well compared to IRI model. It is established in this study that, the IRI electron density at F2 peak (NmF2) gives good GPS TECv prediction when added as an input neuron to the NN.
dc.language en
dc.publisher College of Natural and Applied Sciences, University of Dar es Salaam
dc.subject Neural Network
dc.subject Total Electron Content
dc.subject TEC
dc.subject Global Positioning System
dc.subject GPS
dc.subject GPS TECv
dc.subject NN
dc.subject Eastern Africa region
dc.subject Electron Content Prediction
dc.subject Artificial Neural Networks
dc.subject NN technique
dc.title Total electron content prediction model using the artificial neural networks over the Eastern Africa Region
dc.type Article


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