Two possible approaches for ionospheric forecasting to be employed along with the IRI model

Abstract

Ionospheric forecasting is a popular research area required by telecommunication and navigation system planners and operators. The problem is challenging because ionospheric processes are nonlinear. Data-driven techniques are of particular interest since they overcome most of these difficulties. In this work, two possible ionospheric forecasting approaches have been considered to be employed along with the IRI model. The authors reported these approaches previously. Ionospheric critical frequency values have been forecast using Fuzzy inference and Neural Networks considering the two possible approaches, METU-FNN and METU-NN. In parallel, the foF2 values have been calculated based on the IRI model.