Explainable AI for Cyber-Physical Systems: Issues and Challenges-Reference-Cited by-同舟云学术

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Explainable AI for Cyber-Physical Systems: Issues and Challenges

Published:2024 Issue: Volume:12 Page:73113-73140
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Hoenig Amber¹^ORCID,Roy Kaushik²^ORCID,Acquaah Yaa Takyiwaa²^ORCID,Yi Sun³,Desai Salil S.⁴^ORCID

Affiliation:

1. Department of Computational Data Science and Engineering, North Carolina Agricultural and Technical State University, Greensboro, NC, USA

2. Department of Computer Science, North Carolina Agricultural and Technical State University, Greensboro, NC, USA

3. Department of Mechanical Engineering, North Carolina Agricultural and Technical State University, Greensboro, NC, USA

4. Department of Industrial and Systems Engineering, North Carolina Agricultural and Technical State University, Greensboro, NC, USA

Funder

Office of Naval Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10516690.pdf?arnumber=10516690

Reference77 articles.

1. Explainable unsupervised machine learning for cyber-physical systems;Wickramasinghe;IEEE Access,2021

2. Cyber-physical systems and their security issues

3. Robust Cyber–Physical Systems: Concept, models, and implementation

4. A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems

5. Artificial intelligence and cyber-physical systems: A review and perspectives for the future in the chemical industry;Oliveira;AI,2021

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. Explainable AI in Manufacturing and Industrial Cyber–Physical Systems: A Survey;Electronics;2024-09-03

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