Prediction of ultimate bearing capacity of eccentrically inclined loaded strip footing by ANN, part I

Behera, R.N., Patra, C.R., Sivakugan, N., and Das, B.M. (2013) Prediction of ultimate bearing capacity of eccentrically inclined loaded strip footing by ANN, part I. International Journal of Geotechnical Engineering, 7 (1). pp. 36-44.

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Abstract

Extensive laboratory model tests were conducted on a strip foundation lying over sand bed subjected to an eccentrically inclined load to determine the ultimate bearing capacity. Based on the model test results, a neural network model was developed to predict the reduction factor. This reduction factor (RF) is the ratio of the ultimate bearing capacity of the foundation subjected to an eccentrically inclined load to the ultimate bearing capacity of the foundation subjected to a centric vertical load. Different sensitivity analysis was carried out to evaluate the parameters affecting the reduction factor. Emphasis is given on the construction of neural interpretation diagram, based on the weights of the developed neural network model, to find out direct or inverse effect of input parameters on the output. A prediction model equation is established using the trained weights of the neural network model. The predictions from artificial neural network (ANN), and those from two other approaches, were compared with the laboratory model test results. The ANN model results found to be more accurate and well matched with other results.

Item ID: 26646
Item Type: Article (Research - C1)
ISSN: 1939-7879
Date Deposited: 24 Apr 2013 05:07
FoR Codes: 09 ENGINEERING > 0905 Civil Engineering > 090501 Civil Geotechnical Engineering @ 100%
SEO Codes: 87 CONSTRUCTION > 8702 Construction Design > 870201 Civil Construction Design @ 100%
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