GPS Modeling of the Ionosphere Using Computer Neural Networks

This chapter presents a detailed description to modeling the ionosphere using the method of computer neural networks and data from the GPS (Global Positioning System). The chapter essentially motivates the use of artificial neural networks for ionospheric modeling, and it presents a detailed description of the processes and considerations involved in using artificial neural networks to model the ionosphere. Specific illustration was done using vertical total electron content (VTEC) data from 14 GPS stations in Nigeria that cover the period from years 2011 to 2016, to develop a neural network model of the GPSTEC over Nigeria in space and in time. Sample simulations from the developed model shows that the model was accurate in predicting the VTEC variation patterns in terms of diurnal, seasonal, annual, longitudinal and latitudinal variations. A comparative analysis between the neural network predictions and those of other models like the IRI-Plas and NeQuick showed that predictions from the neural network model were predominantly more accurate.

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