Time series fragmental variation trend anomaly detection method based on a temporal sequential modeling approach
Author:
Affiliation:
1. School of Electronics and Information Engineering, Harbin Institute of Technology,Harbin,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10175865/10175876/10176054.pdf?arnumber=10176054
Reference18 articles.
1. Unmanned Aerial Vehicle Flight Data Anomaly Detection and Recovery Prediction Based on Spatio-Temporal Correlation
2. Efficient on-line anomaly detection for ship systems in operation
3. A Comprehensive Survey on Graph Neural Networks
4. ADMOST: UAV Flight Data Anomaly Detection and Mitigation via Online Subspace Tracking
5. Testing and diagnosis of interconnect faults in cluster-based FPGA architectures
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