A re-engineered multi-thermal ALMANAC algorithm detects eruptive signatures in multi-wavelength EUV data with improved robustness, reduced fragmentation, and better alignment to coronagraph onset times.
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2026 2verdicts
UNVERDICTED 2representative citing papers
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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Multi-Thermal CME Detection with ALMANAC
A re-engineered multi-thermal ALMANAC algorithm detects eruptive signatures in multi-wavelength EUV data with improved robustness, reduced fragmentation, and better alignment to coronagraph onset times.
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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.