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AuthorSenouci, Ahmed B.
Available date2009-11-25T13:05:10Z
Publication Date2000
Publication NameEngineering Journal of Qatar University
CitationEngineering Journal of Qatar University, 2000, Vol. 13, Pages 107-122.
URIhttp://hdl.handle.net/10576/7915
AbstractThis paper presents a backpropagation neural network model for the preliminary design of rectangular concrete beams. The model, which is developed based on the strength design procedure of the American Concrete Institute (ACI), minimizes the beam total cost including the costs of concrete, steel, and shuttering. The backpropagation neural network was successful in accurately capturing the nonlinear characteristics of the strength design procedure. The network adequately learned a set of 375 examples during the training phase. A case study, where a set of 960 new cases were considered, was used to validate the network and to demonstrate the system's generalization and fault-tolerance properties. The network showed good generalization properties since it was able to predict the correct beam depth and steel area with a fair accuracy.
Languageen
PublisherQatar University
SubjectEngineering: Civil Engineering
TitlePreliminary Design Of Reinforced Concrete Beams Using Neural Networks
TypeArticle
Pagination107-122
Volume Number13


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