A CNN-based fusion model trained on multi-instrument solar observations predicts geoeffective CMEs, achieving mean TSS of 0.703 and Brier score of 0.095 via five-fold cross-validation.
Frontiers in Astronomy and Space Sciences , VOLUME=
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SKA's higher sensitivity and bandwidth will enable fuller exploitation of radio methods for measuring CME magnetic fields and improving space weather predictions.
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Deep Learning-Enabled Prediction of Geoeffective CMEs Using SOHO and SDO Observations
A CNN-based fusion model trained on multi-instrument solar observations predicts geoeffective CMEs, achieving mean TSS of 0.703 and Brier score of 0.095 via five-fold cross-validation.
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Role of SKA in Advancing Remote Measurements of Magnetic Fields of Solar Coronal Mass Ejections
SKA's higher sensitivity and bandwidth will enable fuller exploitation of radio methods for measuring CME magnetic fields and improving space weather predictions.