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Título: | Artificial intelligence techniques for prediction of the capacity of RC beams strengthened in shear with external FRP reinforcement |
Autor: | Perera, Ricardo; Arteaga Iriarte, Ángel CSIC; Diego, Ana de CSIC ORCID | Palabras clave: | Shear strengthening FRP Reinforced concrete Neural networks Genetic algorithms |
Fecha de publicación: | abr-2010 | Editor: | Elsevier | Citación: | Composite Structures 92(5): 1169-1175 (2010) | Resumen: | The prediction of the shear capacity of reinforced concrete beams retrofitted in shear by means of externally bonded FRP is very complex as demonstrate the studies carried out up to date. As alternative to the conventional methods two approaches based on artificial intelligence are proposed for the first time. Firstly, the use of neural networks as a means of predicting shear capacity without the need of using complex models and, secondly, the use of genetic algorithms as a means of determining suitably how the shear mechanism works. Predictions obtained with both approaches are compared to experimental values. | Descripción: | 7 páginas, 7 figuras, 3 tablas.-- El Pdf es la versión post-print de autor. | Versión del editor: | http://dx.doi.org/10.1016/j.compstruct.2009.10.027 | URI: | http://hdl.handle.net/10261/40704 | DOI: | 10.1016/j.compstruct.2009.10.027 | ISSN: | 0263-8223 |
Aparece en las colecciones: | (IETCC) Artículos |
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ARTICULOS56611[1].pdf | 716,54 kB | Adobe PDF | Visualizar/Abrir |
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