Use of artificial neural networks for predicting settlement of shallow foundations on cohesionless soils / Mohamed A. Shahin.
Date
2003
Authors
Shahin, Mohamed Amin
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Thesis
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Abstract
This thesis presents research which focuses on the settlement prediction of shallow foundations on cohesionless soils using artificial neural techniques. Previously, many methods have been developed to predict the settlement of shallow foundations, however methods that have the required degree of accuracy and consistency have not yet been developed. In this research artificial neural networks (ANNs) are used in an attempt to obtain more accurate settlement prediction. ANNs are linked with Monte Carlo simulation to provide a stochastic solution for settlement prediction that takes into account the uncertainties associated with settlement analysis. A set of stochastic design charts that provide the designer with the level of risk associated with predicted settlements are developed and provided.
School/Discipline
Dept. of Civil and Environmental Engineering
Dissertation Note
Thesis (Ph.D.)--University of Adelaide, Dept. of Civil and Environmental Engineering, 2003
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This electronic version is made publicly available by the University of Adelaide in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exception. If you are the author of this thesis and do not wish it to be made publicly available or If you are the owner of any included third party copyright material you wish to be removed from this electronic version, please complete the take down form located at: http://www.adelaide.edu.au/legals
Description
"January 2003"
Bibliography: p. 191-208.
xviii, 297 p. : ill. ; 30 cm.
Bibliography: p. 191-208.
xviii, 297 p. : ill. ; 30 cm.