Diagnosis of Device Exception Based on Causality of Device Indicators
Existing intelligent exception diagnosis methods face challenges in unstable feature extraction and difficulty detecting anomalies in high-dimensional spaces. To address these limitations, we propose CGNN—a novel anomaly detection framework integrating causal reasoning with graph neural n...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11048560/ |
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