Artificial neural network analysis of infilled planar frames

dc.contributor.authorBaǧci M.
dc.contributor.authorAltintas G.
dc.date.accessioned2025-04-10T11:17:15Z
dc.date.available2025-04-10T11:17:15Z
dc.date.issued2006
dc.description.abstractIn this study, infilled planar frames have been analysed using an artificial neural network. The data used were provided by a finite element model (FEM) in which nonlinearity of materials and the structural interface were taken into account under increasing lateral load. For the skeleton frame, the panel was modelled by a two-noded frame element and a four-noded isoparametric element respectively. The Von Mises failure criterion was used for the infill wall. Values obtained from FEM were used in training the network established. An artificial neural network (ANN) architecture was chosen in which a multilayer, feed-forward and back-propagation algorithm was used. The controls conducted in the test phase showed that training was satisfactory. The study has proved that the ANN could be successfully used for analysis of infilled planar frames.
dc.identifier.DOI-ID10.1680/stbu.2006.159.1.37
dc.identifier.urihttp://hdl.handle.net/20.500.14701/52485
dc.publisherICE Publishing Ltd
dc.titleArtificial neural network analysis of infilled planar frames
dc.typeConference paper

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