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Artificial neural network prediction of the initial stiffness of semi-rigid beam-to-column connections
dc.contributor.author | Reinosa, J.M. | |
dc.contributor.author | Loureiro, Alfonso | |
dc.contributor.author | Gutierrez, Ruth | |
dc.contributor.author | López López, Manuel | |
dc.date.accessioned | 2023-11-13T14:00:38Z | |
dc.date.available | 2023-11-13T14:00:38Z | |
dc.date.issued | 2023-10 | |
dc.identifier.citation | Reinosa, J. M., A. Loureiro, R. Gutierrez, and M. Lopez. 2023. “Artificial Neural Network Prediction of the Initial Stiffness of Semi-Rigid Beam-to-Column Connections,” Structures 56, 56: 104904. https://doi.org/10.1016/j.istruc.2023.104904. | es_ES |
dc.identifier.issn | 2352-0124 | |
dc.identifier.uri | http://hdl.handle.net/2183/34171 | |
dc.description.abstract | [Abstract]: Joints are significant components in the design and construction of steel structures. The characteristic parameters of the connections must be reproduced in a reliable way to represent the actual behaviour of a structure. Accordingly, the study of semi-rigid joints is essential to better understand this issue. Among the different types of semi-rigid joints, angle connections stand out as a suitable solution in many cases. This paper presents a methodology using artificial neural networks for predicting the initial rotational stiffness of major axis symmetrical angle connections according to the Eurocode description. A consistent stiffness database was developed from the existing data in the Steel Connection Data Bank. Then, the database was cleansed to provide with a robust training set. Different network architectures were analysed until a topology that showed a good performance and generalisation features was obtained. The network was successfully checked with some saved tests from the database and with off-database tests; the network could be reliably used within the range of the training input parameters. | es_ES |
dc.description.sponsorship | Ministerio de Ciencia e Innovación; PID2020-113895GBC31 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.uri | https://doi.org/10.1016/j.istruc.2023.104904 | es_ES |
dc.rights | Attribution-NonCommercial-NoDerivs 4.0 International | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject | Angle connections | es_ES |
dc.subject | Semi-rigid joints | es_ES |
dc.subject | Initial stiffness | es_ES |
dc.subject | Artificial neural networks | es_ES |
dc.title | Artificial neural network prediction of the initial stiffness of semi-rigid beam-to-column connections | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Structures | es_ES |
UDC.volume | 56 | es_ES |
dc.identifier.doi | https://doi.org/10.1016/j.istruc.2023.104904 |