Abstract EXtreme Gradient Boosting over Decision Trees (XGBoost or XGBDT) is a powerful
tool to model a wide range of processes. We propose a new approach to create a global …

To further improve the short-term forecasting ability of the critical frequency of the
ionosphere F2 layer (foF2), a sample entropy (SE) optimized deep learning (DL) long-short …

The variation of the ionospheric parameters has a crucial role in space weather,
communication, and navigation applications. In this research, we analyze the prediction …

To achieve accurate forecasting of the peak height of the ionospheric F2 layer (hmF2), we
propose a hybrid deep learning model of improved seagull optimization algorithm (ISOA) …

Monitoring of critical frequency variation in the ionospheric F2 layer (foF2) has lately
received considerable attention for the frequency selection in skywave communication …

The total electron content (TEC) of the ionosphere at low latitudes is significantly influenced
by solar-geomagnetic activity and seasonal variations. Traditional ionospheric models often …

The ionosphere plays an important role in satellite navigation, radio communication, and
space weather prediction. However, it is still a challenging mission to develop a model with …

In order to improve the prediction accuracy of ionospheric total electron content (TEC), a
combined intelligent prediction model (MMAdapGA-BP-NN) based on a multi-mutation, multi …

The ionospheric F2 layer is the essential layer in the propagation of high-frequency radio
waves, and the peak electron density height of the ionospheric F2 layer (hmF2) is one of the …

Ionospheric delay has a severe effect on reducing the accuracy of positioning and
navigation of single-frequency receivers. Therefore, it is necessary to construct a precise …