Journal
CONSTRUCTION AND BUILDING MATERIALS
Volume 23, Issue 10, Pages 3225-3232Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.conbuildmat.2009.06.002
Keywords
Circular RC column; Shear strength; Neural networks; Scaled conjugate gradient algorithm
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The objective of this study is to investigate the adequacy of neural networks (NN) as a quicker, more secure and more robust method to determine the shear strength of circular reinforced concrete columns. In the application of the NN model, a multilayer perceptron (MLP) with a back-propagation (BP) algorithm is employed using a scaled conjugate gradient. NN model is developed, trained and tested through a based MATLAB program. The data used for training and testing NN model are gathered from literature. NN based model outputs are compared with ACI, ATC-32, ASCE and CALTRANS codes outcomes on the basis of the experimental results. This comparison demonstrated that the NN based model is highly successful to determine the shear strength of circular reinforced concrete columns. (C) 2009 Elsevier Ltd. All rights reserved.
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