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25 January 2022
Deep Learning in Nuclear Industry: A Survey
Jiancheng Lv(
)
)
Keywords:
Artificial Intelligence (AI), research status, nuclear industry, Deep Learning (DL), development trend
Cite this article:
Tang C, Yu C, Gao Y, et al.
Deep Learning in Nuclear Industry: A Survey.
Big Data Mining and Analytics,
2022, 5(2): 140-160.
https://doi.org/10.26599/BDMA.2021.9020027
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As a high-tech strategic emerging comprehensive industry, the nuclear industry is committed to the research, production, and processing of nuclear fuel, as well as the development and utilization of nuclear energy. Nowadays, the nuclear industry has made remarkable progress in the application fields of nuclear weapons, nuclear power, nuclear medical treatment, radiation processing, and so on. With the development of artificial intelligence and the proposal of "Industry 4.0", more and more artificial intelligence technologies are introduced into the nuclear industry chain to improve production efficiency, reduce operation cost, improve operation safety, and realize risk avoidance. Meanwhile, deep learning, as an important technology of artificial intelligence, has made amazing progress in theoretical and applied research in the nuclear industry, which vigorously promotes the development of informatization, digitization, and intelligence of the nuclear industry. In this paper, we first simply comb and analyze the intelligent demand scenarios in the whole industrial chain of the nuclear industry. Then, we discuss the data types involved in the nuclear industry chain. After that, we investigate the research status of deep learning in the application fields corresponding to different data types in the nuclear industry. Finally, we discuss the limitation and unique challenges of deep learning in the nuclear industry and the future direction of the intelligent nuclear industry.
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Deep Learning in Nuclear Industry: A Survey
Jiancheng Lv(
)
)
Abstract
As a high-tech strategic emerging comprehensive industry, the nuclear industry is committed to the research, production, and processing of nuclear fuel, as well as the development and utilization of nuclear energy. Nowadays, the nuclear industry has made remarkable progress in the application fields of nuclear weapons, nuclear power, nuclear medical treatment, radiation processing, and so on. With the development of artificial intelligence and the proposal of "Industry 4.0", more and more artificial intelligence technologies are introduced into the nuclear industry chain to improve production efficiency, reduce operation cost, improve operation safety, and realize risk avoidance. Meanwhile, deep learning, as an important technology of artificial intelligence, has made amazing progress in theoretical and applied research in the nuclear industry, which vigorously promotes the development of informatization, digitization, and intelligence of the nuclear industry. In this paper, we first simply comb and analyze the intelligent demand scenarios in the whole industrial chain of the nuclear industry. Then, we discuss the data types involved in the nuclear industry chain. After that, we investigate the research status of deep learning in the application fields corresponding to different data types in the nuclear industry. Finally, we discuss the limitation and unique challenges of deep learning in the nuclear industry and the future direction of the intelligent nuclear industry.
Keywords:
Artificial Intelligence (AI), research status, nuclear industry, Deep Learning (DL), development trend
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Publication history
Received: 08 December 2021
Accepted: 15 December 2021
Published:
25 January 2022
Issue date: June 2022
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© The author(s) 2022.
Acknowledgements
This work was supported in part by the State Key Program of National Science Foundation (No. 61836006), the National Natural Science Fund for Distinguished Young Scholar (No. 61625204), the National Natural Science Foundation of China (Nos. 62106161 and 61602328), as well as the Key Research and Development Project of Sichuan (No. 2019YFG0494).
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