Neural networks assessment of beam-to-column joints
This paper proposes the use of artificial neural networks to predict the flexural resistance and initial stiffness of beam-to-column steel joints using the back propagation supervised learning algorithm. Three types of steel beam-to-column joints were investigated: welded, endplate and bolted with top, seat and double web angles, respectively. The neural networks results proved to be consistent with experimental and design code reference values.
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| Main Authors: | , , , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM
2005
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| Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-58782005000300015 |
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