Anomaly detection of industrial state quantity time-Series data based on correlation and long short-term memory
Author:
Affiliation:
1. College of Computer and Science National University of Defense Technology, Changsha, China
2. Key Laboratory of Space Launching Site Reliability Technology, Haikou, China
Funder
the Independent and open subject fund
State Key Laboratory of High-Performance Computing
the National Key Research and Development Program of China
Publisher
Informa UK Limited
Subject
Artificial Intelligence,Human-Computer Interaction,Software
Link
https://www.tandfonline.com/doi/pdf/10.1080/09540091.2022.2092594
Reference36 articles.
1. Chalapathy, R. & Chawla, S. (2019). Deep learning for anomaly detection: A survey. arXiv preprint arXiv:1901.03407.
2. Discrete wavelet transform-based time series analysis and mining
3. A test for second-order stationarity of a time series based on the discrete Fourier transform
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