[Other] Geiger-Nuttall systematics for汐decay with neutron-proton double-shell and valence-nucleon effects |
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Machine Learning-Driven Anomaly Detection and Forecasting for Euclid Space Telescope Operations
30
Building and verifying end-to-end deep learning engines to detect anomalies in spacecraft telemetry using satellite digital twins
30
Proposal of Health Monitoring Method using Satellite Health Map Based on Feature Representation
20
An Integrated Framework Based on Deep Autoregressive Models for Satellite Telemetry Parameter Forecasting, Imputation and Anomaly Detection
30
Optimized Machine Learning-Based Strategies for On-Board S/C Failure Detection: Software Integration and Testing on a Space-Qualified Processor