Deep Learning in Nuclear Industry: A Survey
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...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Tsinghua University Press
2022-06-01
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| Series: | Big Data Mining and Analytics |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2021.9020027 |
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| _version_ | 1832573634205450240 |
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| author | Chenwei Tang Caiyang Yu Yi Gao Jianming Chen Jiaming Yang Jiuling Lang Chuan Liu Ling Zhong Zhenan He Jiancheng Lv |
| author_facet | Chenwei Tang Caiyang Yu Yi Gao Jianming Chen Jiaming Yang Jiuling Lang Chuan Liu Ling Zhong Zhenan He Jiancheng Lv |
| author_sort | Chenwei Tang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-93e933753aeb445fa28e33c5a2e709dd |
| institution | Kabale University |
| issn | 2096-0654 |
| language | English |
| publishDate | 2022-06-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj-art-93e933753aeb445fa28e33c5a2e709dd2025-02-02T03:45:09ZengTsinghua University PressBig Data Mining and Analytics2096-06542022-06-015214016010.26599/BDMA.2021.9020027Deep Learning in Nuclear Industry: A SurveyChenwei Tang0Caiyang Yu1Yi Gao2Jianming Chen3Jiaming Yang4Jiuling Lang5Chuan Liu6Ling Zhong7Zhenan He8Jiancheng Lv9College of Computer Science, Sichuan University, Chengdu 610065, ChinaCollege of Computer Science, Sichuan University, Chengdu 610065, ChinaCollege of Computer Science, Sichuan University, Chengdu 610065, ChinaCollege of Computer Science, Sichuan University, Chengdu 610065, ChinaCollege of Computer Science, Sichuan University, Chengdu 610065, ChinaCollege of Computer Science, Sichuan University, Chengdu 610065, ChinaCollege of Computer Science, Sichuan University, Chengdu 610065, ChinaCollege of Computer Science, Sichuan University, Chengdu 610065, ChinaCollege of Computer Science, Sichuan University, Chengdu 610065, ChinaCollege of Computer Science, Sichuan University, Chengdu 610065, ChinaAs 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.https://www.sciopen.com/article/10.26599/BDMA.2021.9020027nuclear industryartificial intelligence (ai)deep learning (dl)research statusdevelopment trend |
| spellingShingle | Chenwei Tang Caiyang Yu Yi Gao Jianming Chen Jiaming Yang Jiuling Lang Chuan Liu Ling Zhong Zhenan He Jiancheng Lv Deep Learning in Nuclear Industry: A Survey Big Data Mining and Analytics nuclear industry artificial intelligence (ai) deep learning (dl) research status development trend |
| title | Deep Learning in Nuclear Industry: A Survey |
| title_full | Deep Learning in Nuclear Industry: A Survey |
| title_fullStr | Deep Learning in Nuclear Industry: A Survey |
| title_full_unstemmed | Deep Learning in Nuclear Industry: A Survey |
| title_short | Deep Learning in Nuclear Industry: A Survey |
| title_sort | deep learning in nuclear industry a survey |
| topic | nuclear industry artificial intelligence (ai) deep learning (dl) research status development trend |
| url | https://www.sciopen.com/article/10.26599/BDMA.2021.9020027 |
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