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Geotechnical and Geological Engineering
Erschienen in: Geotechnical and Geological Engineering 2/2016

10.12.2015 | Original paper

Reliability Analysis of Quick Sand Condition

verfasst von: Pijush Samui, Pradeep Kurup, S. Dhivya, J. Jagan

Erschienen in: Geotechnical and Geological Engineering | Ausgabe 2/2016

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Abstract

First order reliability method (FORM) is generally used for reliability analysis in geotechnical engineering. This article adopts generalized regression neural network (GRNN) based FORM, Gaussian process regression (GPR) based FORM and multivariate adaptive regression spline (MARS) based FORM for reliability analysis of quick sand condition. GRNN is related to the radial basis function (RBF) network. GPR is developed based on probabilistic framework. MARS is a nonparametric regression technique. A comparative study has been carried out between the developed models. The performance of GPR based FORM and MARS based FORM match well with the FORM. This article gives the alternative methods for reliability analysis of quick sand condition.
Vorheriger Artikel Experimental Investigation of Frictional Behavior Between Cohesive Soils and Solid Materials Using Direct Shear Apparatus
Nächster Artikel Variability and Correlation of Strength Parameters Inferred from Direct Shear Tests

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Metadaten
Titel
Reliability Analysis of Quick Sand Condition
verfasst von
Pijush Samui
Pradeep Kurup
S. Dhivya
J. Jagan
Publikationsdatum
10.12.2015
Verlag
Springer International Publishing
Erschienen in
Geotechnical and Geological Engineering / Ausgabe 2/2016
Print ISSN: 0960-3182
Elektronische ISSN: 1573-1529
DOI
https://doi.org/10.1007/s10706-015-9967-4

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