Solar Flare Prediction

Solar flare prediction aims to forecast the occurrence and intensity of these powerful solar eruptions, crucial for mitigating their impact on space-based and terrestrial technologies. Current research heavily utilizes deep learning models, such as convolutional neural networks (CNNs) and long short-term memory networks (LSTMs), often incorporating techniques like attention mechanisms and post-hoc explainability methods to improve prediction accuracy and understand model decision-making. A key focus is on improving predictions of near-limb flares and leveraging both full-disk and active region-specific data for more robust forecasting. These advancements are vital for enhancing space weather forecasting capabilities and protecting critical infrastructure from solar disturbances.