Cite
Adversarial training of LSTM-ED based anomaly detection for complex time-series in cyber-physical-social systems.
MLA
Zhu, Haiqi, et al. “Adversarial Training of LSTM-ED Based Anomaly Detection for Complex Time-Series in Cyber-Physical-Social Systems.” Pattern Recognition Letters, vol. 164, Dec. 2022, pp. 132–39. EBSCOhost, https://doi.org/10.1016/j.patrec.2022.10.017.
APA
Zhu, H., Liu, S., & Jiang, F. (2022). Adversarial training of LSTM-ED based anomaly detection for complex time-series in cyber-physical-social systems. Pattern Recognition Letters, 164, 132–139. https://doi.org/10.1016/j.patrec.2022.10.017
Chicago
Zhu, Haiqi, Shaohui Liu, and Feng Jiang. 2022. “Adversarial Training of LSTM-ED Based Anomaly Detection for Complex Time-Series in Cyber-Physical-Social Systems.” Pattern Recognition Letters 164 (December): 132–39. doi:10.1016/j.patrec.2022.10.017.