Forecasting SEP Events During Solar Cycles 23 and 24 Using Interpretable Machine Learning

arXiv:2403.02536v1 Announce Type: cross
Abstract: Prediction of the Solar Energetic Particle (SEP) events garner increasing interest as space missions extend beyond Earth's protective magnetosphere. These events, which are, in most cases, products of magnetic reconnection-driven processes during solar flares or fast coronal-mass-ejection-driven shock waves, pose significant radiation hazards to aviation, space-based electronics, and particularly, space exploration. In this work, we utilize the recently developed dataset that combines the Solar Dynamics Observatory/Helioseismic and Magnetic Imager's (SDO/HMI) Space weather HMI Active Region …

abstract arxiv astro-ph.sr beyond cases cs.lg earth events forecasting machine machine learning particle physics.space-ph prediction processes products solar space space missions type