1 citations · 1 across the 1 of their papers we have counts for
5 papers
Review of Machine Learning Models for Solar Energetic Particle Prediction
Spiridon Kasapis, Pouya Hosseinzadeh, Kathryn Whitman +73
Solar energetic particle (SEP) events have attracted increasing attention due to their significant radiation hazards for aviation, spacecraft electronics, and human missions beyond…
Quantifying the Effects of Parameters in Widespread SEP Events with EPREM
Matthew A. Young, Bala Poduval
The Energetic Particle Radiation Environment Model (EPREM) solves the focused transport equation (FTE) on a Lagrangian grid in a frame co-moving with the solar wind plasma and simu…
IonCast: A Deep Learning Framework for Forecasting Ionospheric Dynamics
Halil S. Kelebek, Linnea M. Wolniewicz, Michael D. Vergalla +8
The ionosphere is a critical component of near-Earth space, shaping GNSS accuracy, high-frequency communications, and aviation operations. For these reasons, accurate forecasting a…
Forecasting the Ionosphere from Sparse GNSS Data with Temporal-Fusion Transformers
Giacomo Acciarini, Simone Mestici, Halil Kelebek +7
The ionosphere critically influences Global Navigation Satellite Systems (GNSS), satellite communications, and Low Earth Orbit (LEO) operations, yet accurate prediction of its vari…
Energetic Ion Composition as a Means of Investigating the Physical Origins of Alpha Particle Heavy Magnetic Switchbacks
Emily McDougall, Bala Poduval
Magnetic switchbacks are of continuing interest to the scientific community due to the fact that the phenomenon has not been completely understood. Although most of the research in…