LSTM learning with Bayesian and Gaussian processing for anomaly detection in industrial IoT

D Wu, Z Jiang, X Xie, X Wei, W Yu… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The data generated by millions of sensors in the industrial Internet of Things (IIoT) are
extremely dynamic, heterogeneous, and large scale and pose great challenges on the real …

LSTM Learning with Bayesian and Gaussian Processing for Anomaly Detection in Industrial IoT

D Wu, Z Jiang, X Xie, X Wei… - IEEE Transactions on …, 2020 - publications.aston.ac.uk
The data generated by millions of sensors in Industrial Internet of Things (IIoT) is extremely
dynamic, heterogeneous, and large scale. It poses great challenges on the real-time …

LSTM learning with Bayesian and Gaussian processing for anomaly detection in industrial IoT

D Wu, Z Jiang, X Xie, X Wei, W Yu… - IEEE Transactions on …, 2020 - wrap.warwick.ac.uk
The data generated by millions of sensors in Industrial Internet of Things (IIoT) is extremely
dynamic, heterogeneous, and large scale. It poses great challenges on the real-time …

[引用][C] LSTM Learning With Bayesian and Gaussian Processing for Anomaly Detection in Industrial IoT

ZJ Di Wu, X Xie, X Wei, W Yu, R Li - IEEE Transactions on Industrial …, 2020 - cir.nii.ac.jp
LSTM Learning With Bayesian and Gaussian Processing for Anomaly Detection in Industrial
IoT | CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 検索 …

LSTM Learning with Bayesian and Gaussian Processing for Anomaly Detection in Industrial IoT

D Wu, Z Jiang, X Xie, X Wei, W Yu… - IEEE Transactions on …, 2020 - research.aston.ac.uk
The data generated by millions of sensors in Industrial Internet of Things (IIoT) is extremely
dynamic, heterogeneous, and large scale. It poses great challenges on the real-time …