Robust Dynamic Latent Variable Model for Dynamic Process Monitoring With Missing Data in Cyber-Physical Systems-Reference-Cited by-同舟云学术

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Robust Dynamic Latent Variable Model for Dynamic Process Monitoring With Missing Data in Cyber-Physical Systems

Published:2023 Issue: Volume:1 Page:227-235
ISSN:2832-7004
Container-title:IEEE Transactions on Industrial Cyber-Physical Systems
language:
Short-container-title:Trans. Ind. Cyb-Phy. Sys.

Author:

Zhou Le¹^ORCID,Yu Lixinqian²^ORCID,Hou Beiping¹^ORCID,Zheng Hongbo¹^ORCID,Wu Zheng-Guang³^ORCID

Affiliation:

1. School of Automation and Electrical Engineering, Zhejiang University of Science & Technology, Hangzhou, China

2. Faculty of Engineering and IT, University of Melbourne, Melbourne, Australia

3. National Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, China

Funder

National Natural Science Foundation of China

Key Research and Development Project of Zhejiang Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9984155/10053577/10265131.pdf?arnumber=10265131

Reference26 articles.

1. Autoregressive Dynamic Latent Variable Models for Process Monitoring

2. A New Method of Dynamic Latent-Variable Modeling for Process Monitoring

3. Review and big data perspectives on robust data mining approaches for industrial process modeling with outliers and missing data

4. Principal Component Analysis of Process Datasets with Missing Values

5. Data-based linear Gaussian state-space model for dynamic process monitoring

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