Subject
Mechanical Engineering,Waste Management and Disposal,Safety, Risk, Reliability and Quality,General Materials Science,Nuclear Energy and Engineering,Nuclear and High Energy Physics
Reference30 articles.
1. Development of good practice guidance for quantification of thermal-hydraulic code model input uncertainty;Baccou;Nucl. Eng. Des.,2019
2. A machine learning strategy with restricted sliding windows for real-time assessment of accident conditions in nuclear power plants;Chung;Nucl. Eng. Des.,2021
3. Glaeser, H. (GRS), Bazin, P. (CEA), Baccou, J. (IRSN), Chojnacki, E. (IRSN), Destercke, S. (IRSN), 2011. BEMUSE Phase VI Report Status report on the area, classification of the methods, conclusions and recommendations. Csni. https://doi.org/NEA/CSNI/R(2011)4 JT03299065.
4. Nuclear energy system’s behavior and decision making using machine learning;Gomez Fernandez;Nucl. Eng. Des.,2017
5. Using Machine Learning Methods to Predict Bias in Nuclear Criticality Safety;Grechanuk;J. Comput. Theor. Transp.,2018
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