Supervised learning for finite element analysis of holes under biaxial load
This paper presents a novel approach of using supervised learning with a shallow neural network to increase the efficiency for the finite element analysis of holes under biaxial load. The objective of this approach is to reduce the number of elements in the finite element analysis while maintaining...
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| Materiálatiipa: | Final Year Project (FYP) |
| Giella: | English |
| Almmustuhtton: |
Nanyang Technological University
2020
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| Liŋkkat: | https://hdl.handle.net/10356/139113 |