Total Electron Content Prediction Model using the Artificial Neural Networks over the Eastern Africa Region

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.Keywords: GPS; GPS TECv; Total Electron Content; Neural Networ

Total electron content derived from global positioning system during solar maximum of 2012-2013 over the eastern part of the African sector

This work presents results of diurnal, seasonal and latitudinal variations of vertical Total Electron Content (TECv) derived from GPS receivers at four locations, [Dodoma (6.19oS, 35.75oE), Mzuzu (11.43oS, 34.01oE), Zomba (15.38oS, 35.33oE) and Tete (16.15oS, 33.58oE)] during the solar maximum period of 2012 – 2013. The receivers are located directly below the EIA and at approximately the same longitude, ~ (33 – 3 oE) within the eastern part of the African sector. Diurnal and latitudinal variations of TECv are presented for an average of the five (5) quietest days of each of the four seasons: March equinox, June solstice, September equinox and December solstice; for the seasonal variations all months in a year were considered. Results showed that TECv is characterized by consistent minimum diurnal variations during presunrise hours, rises steeply during the sunrise period to the maximum peak during the daytime, followed by a decrease to a minimum during nighttime. The values of TECv from all stations used and for both years (2012 and 2013) showed semiannual variations. Our study also showed that, the day maximum value of the TECv decreased significantly with the increase in latitude.Keywords: Global Positioning System, Total Electron Conten