Review of Machine Learning Models for Solar Energetic Particle Prediction

The article reviews various machine learning models developed for predicting solar energetic particle (SEP) events, highlighting the transition from traditional physics-based simulations to ML approaches. It examines different architectures, datasets, and methodologies employed in these models, aiming to provide insights and recommendations for enhancing prediction accuracy. This work is significant for practitioners as it consolidates knowledge on effective ML strategies for SEP prediction, which is crucial for mitigating radiation hazards in space exploration and technology.