Ensemble Machine Learning model for Ionospheric TEC Prediction over Low-Latitude Regions

Predicting ionospheric TEC enhances GPS and NavIC navigation by countering solar and magnetic field effects. We introduced an ensemble of Random Forest, AdaBoost and XgBoost for TEC prediction in central India’s low-latitude region. Equatorial Ionization Anomaly makes low-latitude TEC forecasting challenging. Our novel work is to make an ensemble modelling algorithm for strengthening and improved performance.This approach not only capitalizes on the unique strengths of each algorithm but also produces a combination effect that enhances the overall performance. It is possible to utilize TEC gradients from Radio Interferometers like GMRT to reconstruct smaller-scale changes using these models [1].