A new data-driven framework for progressive anomaly event alerts in spacecraft based on reconstruction discrepancy

Author:

Liu Ming,Xia Qing,Qiu Shi

Publisher

Elsevier BV

Reference35 articles.

1. Usad: Unsupervised anomaly detection on multivariate time series;Audibert,2020

2. Bai, S., Kolter, J.Z., Koltun, V., 2018. An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271.

3. Imbalanced satellite telemetry data anomaly detection model based on bayesian lstm;Chen;Acta Astronaut.,2021

4. An unsupervised root cause analysis method for satellite on-orbit anomalies based on causal discovery;Chen;Adv. Space Res.,2023

5. Chung, J., Gulcehre, C., Cho, K. et al., 2014. Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555.

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