Guest Editorial Machine Learning for Resilient Industrial Cyber-Physical Systems-Reference-Cited by-同舟云学术

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Guest Editorial Machine Learning for Resilient Industrial Cyber-Physical Systems

Published:2023-01 Issue:1 Volume:20 Page:3-4
ISSN:1545-5955
Container-title:IEEE Transactions on Automation Science and Engineering
language:
Short-container-title:IEEE Trans. Automat. Sci. Eng.

Author:

Hu Shiyan¹,Chen Yiran²^ORCID,Zhu Qi³^ORCID,Colombo Armando Walter⁴^ORCID

Affiliation:

1. School of Electronics and Computer Science, University of Southampton, Southampton, U.K.

2. Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA

3. Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, USA

4. Department of Electrotechnical and Industrial Informatics, University of Applied Sciences Emden/Leer, Emden, Germany

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/8856/10007430/10007535.pdf?arnumber=10007535

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The role of machine learning in improving power distribution systems resilience;Future Modern Distribution Networks Resilience;2024

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