AI RESEARCH
Deep Learning-Enabled Prediction of Geoeffective CMEs Using SOHO and SDO Observations
arXiv CS.LG
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ArXi:2605.24748v1 Announce Type: cross Understanding and forecasting the geoeffectiveness of a coronal mass ejection (CME) is crucial for protecting infrastructure in the near-Earth space environment and on Earth. In this study, we present a novel fusion model to forecast the geoeffectiveness of CME events. Our model combines convolutional neural networks for feature learning and a prediction network for feature fusion and event classification.