E-CAAD anomaly detection model trained on J-TEXT transfers to EAST via adaptive learning from scratch and threshold adjustment, reaching 85.88% TPR and 6.15% FPR from first discharge.
Implementation of the Disruption Predictor APODIS in JET's Real -Time Network Using the MARTe Framework
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Adaptive Anomaly Detection Disruption Prediction Starting from First Discharge on Tokamak
E-CAAD anomaly detection model trained on J-TEXT transfers to EAST via adaptive learning from scratch and threshold adjustment, reaching 85.88% TPR and 6.15% FPR from first discharge.