Estimation of effective stress parameter of unsaturated soils by using artificial neural networks

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dc.contributor.authorKayadelen, C.
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2008
dc.departmentNiğde ÖHÜ
dc.description.abstractGreat efforts are required for determination of the effective stress parameter chi, applying the unsaturated testing procedure, since unsaturated soils that have the three-phase system exhibit complex mechanical behavior. Therefore, it seems more reasonable to use the empirical methods for estimation of chi. The objective of this study is to investigate the practicability of using artificial neural networks (ANNs) to model the complex relationship between basic soil parameters, matric suction and the parameter chi. Five ANN models with different input parameters were developed. Feed-forward back propagation was applied in the analyses as a learning algorithm. The data collected from the available literature were used for training and testing the ANN models. Furthermore, unsaturated triaxial tests were carried out under drained condition on compacted specimens. ANN models were validated by a part of data sets collected from the literature and data obtained from the current study, which were not included in the training phase. The analyses showed that the results obtained from ANN models are in satisfactory agreement with the experimental results and ANNs can be used as reliable tool for prediction of chi. Copyright (C) 2007 John Wiley & Sons, Ltd.
dc.identifier.doi10.1002/nag.660
dc.identifier.endpage1106
dc.identifier.issn0363-9061
dc.identifier.issue9
dc.identifier.scopus2-s2.0-46249122304
dc.identifier.scopusqualityQ1
dc.identifier.startpage1087
dc.identifier.urihttps://dx.doi.org/10.1002/nag.660
dc.identifier.urihttps://hdl.handle.net/11480/5234
dc.identifier.volume32
dc.identifier.wosWOS:000257088900004
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorKayadelen, C.
dc.language.isoen
dc.publisherJOHN WILEY & SONS LTD
dc.relation.ispartofINTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjecteffective stress
dc.subjectunsaturated soil
dc.subjectmatric suction
dc.subjectartificial neural networks
dc.subjectfeed-forward back propagation
dc.titleEstimation of effective stress parameter of unsaturated soils by using artificial neural networks
dc.typeArticle

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