Predicting the energetic proton flux with a machine learning regression algorithm

arXiv:2406.12730v1 Announce Type: cross
Abstract: The need of real-time of monitoring and alerting systems for Space Weather hazards has grown significantly in the last two decades. One of the most important challenge for space mission operations and planning is the prediction of solar proton events (SPEs). In this context, artificial intelligence and machine learning techniques have opened a new frontier, providing a new paradigm for statistical forecasting algorithms. The great majority of these models aim to predict the occurrence of …

abstract algorithm arxiv astro-ph.im astro-ph.sr challenge context cs.lg events hazards important machine machine learning mission monitoring operations physics.space-ph planning prediction proton real-time regression solar space systems type weather