FEW-GROUP CROSS SECTIONS MODELING BY ARTIFICIAL NEURAL NETWORKS
This work deals with the modeling of homogenized few-group cross sections by Artificial Neural Networks (ANN). A comprehensive sensitivity study on data normalization, network architectures and training hyper-parameters specifically for Deep and Shallow Feed Forward ANN is presented. The optimal mod...
| 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_06029.pdf |