Publication Type : Journal Article
Publisher : Inderscience
Source : International Journal of Design Engineering, Inderscience, Volume 3, Issue 1, p.77-96 (2010)
Url : http://www.inderscienceonline.com/doi/abs/10.1504/IJDE.2010.032823
Keywords : ANN, Artificial neural networks, Backpropagation, design engineering, equivalent strut method, evolutionary computation, failure load, infilled frames, lateral loading, Testing, Training
Campus : Coimbatore
School : School of Engineering
Department : Civil
Year : 2010
Abstract : A neural network model to determine the failure load and drift of infilled frames under lateral loading is developed in the present paper. The backpropagation neural network is used to evaluate the failure criteria on the infilled frames using the analytically generated data. Training of the network is done by considering the aspect ratio, number of bays, area of column, area of beam, grade of concrete, grade of steel used for the construction and a non-dimensional parameter λh as the input parameters. To validate the efficacy of the model, an experimental investigation was carried out and the results are compared with that obtained using the ANN model. The experimentation is carried out under the same conditions used for the generation of the analytical data. The agreement was found to be good.
Cite this Research Publication : ANN, Artificial neural networks, Backpropagation, design engineering, equivalent strut method, evolutionary computation, failure load, infilled frames, lateral loading, Testing, Training