John Bosco Habarulema

TL;DR: In this paper, the authors presented a feasibility study for the development of a Neural Network (NN) based model for the prediction of South African GPS derived total electron content (TEC), which is one of the physical quantities that can be derived from GPS data and provides an indication of ionospheric variability.

TL;DR: In this paper, the authors presented a feasibility study for the development of a Neural Network (NN) based model for the prediction of South African GPS derived total electron content (TEC) which can be considered as the ionosphere's measure of ionisation.

TL;DR: In this article, the potential extrapolation capabilities and limitations of ANNs are investigated by generating total electron content (TEC) predictions using the regional southern Africa total electron prediction (SATECP) model based on the Global Positioning System (GPS) data and ANNs with the aid of multiple inputs intended to enable the software to learn and correlate the relationship between their variations and the target parameter.

TL;DR: In this paper, GPS data derived from dual frequency receivers located at African equatorial and midlatitudes is used to study the solar wind effects on the Earth's environment and crucial practical impacts on technological systems.

TL;DR: In this article, total electron content (TEC) measurements (rate of TEC change, ROT) were used to examine the presence of ionospheric irregularities over four low-latitude stations in the African sector, a region that has been less studied.