Advancements and challenges of machine learning and deep learning in autonomous control of nuclear reactors
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Published:2025-12
Issue:
Volume:223
Page:111643
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ISSN:0306-4549
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Container-title:Annals of Nuclear Energy
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language:en
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Short-container-title:Annals of Nuclear Energy
Author:
Hsieh Hui-YuORCID,
Tsvetkov Pavel
Reference150 articles.
1. Abdelfattah, H., Kotb, S. A., Esmail, M., & Mosaad, M. I. (2022). Adaptive Neuro-Fuzzy Self Tuned-PID Controller for Stabilization of Core Power in a Pressurized Water Reactor. 2022, 3(1), 18. doi:10.31763/ijrcs.v3i1.710.
2. A robust diagnosis method specifically for similar faults in nuclear power plant multi-systems based on data segmentation and stacked convolutional autoencoders;Ai;Ann. Nucl. Energy,2025
3. Automation levels for nuclear reactor operations: A revised perspective;Alberti;Prog. Nucl. Energy,2023
4. An introduction to autonomous control systems;Antsaklis;IEEE Control Syst. Mag.,1991
5. Dynamic modeling and intelligent hybrid control of pressurized water reactor NPP power transient operation;Ayele Ejigu;Ann. Nucl. Energy,2022