MODELING NUCLEAR DATA UNCERTAINTIES USING DEEP NEURAL NETWORKS
A new concept using deep learning in neural networks is investigated to characterize the underlying uncertainty of nuclear data. Analysis is performed on multi-group neutron cross-sections (56 energy groups) for the GODIVA U-235 sphere. A deep model is trained with cross-validation using 1000 nuclea...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2021-01-01
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| Series: | EPJ Web of Conferences |
| Subjects: | |
| Online Access: | https://www.epj-conferences.org/articles/epjconf/pdf/2021/01/epjconf_physor2020_15016.pdf |