1.College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
2.The Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China
3.Fujian Fuqing Nuclear Power Co., Ltd., Fujian 350318, China
xuyongxmu@gmail.com
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纸质出版日期:2022-10,
网络出版日期:2022-10-11,
收稿日期:2022-03-05,
修回日期:2022-08-12,
录用日期:2022-08-21
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引用本文
Anomaly detection of control rod drive mechanism using long short-term memory based autoencoder and extreme gradient boosting[J]. 核技术(英文版), 2022, 33(10):127
Jing Chen, Ze-Shi Liu, Hao Jiang, et al. Anomaly detection of control rod drive mechanism using long short-term memory based autoencoder and extreme gradient boosting[J]. Nuclear Science and Techniques, 2022, 33(10):127
Anomaly detection of control rod drive mechanism using long short-term memory based autoencoder and extreme gradient boosting[J]. 核技术(英文版), 2022, 33(10):127 DOI: 10.1007/s41365-022-01111-0.
Jing Chen, Ze-Shi Liu, Hao Jiang, et al. Anomaly detection of control rod drive mechanism using long short-term memory based autoencoder and extreme gradient boosting[J]. Nuclear Science and Techniques, 2022, 33(10):127 DOI: 10.1007/s41365-022-01111-0.
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