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Reliability Analysis of Quick Sand Condition

Samui, Pijush / Kurup, Pradeep / Dhivya, S. / Jagan, J.

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.

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Reliability Analysis of Quick Sand Condition

Samui, Pijush / Kurup, Pradeep / Dhivya, S. / Jagan, J.

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.

Reliability Analysis of Quick Sand Condition

Samui, Pijush / Kurup, Pradeep / Dhivya, S. / Jagan, J.

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.

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Title:

Reliability Analysis of Quick Sand Condition

Contributors:

Samui, Pijush (author) / Kurup, Pradeep (author) / Dhivya, S. (author) / Jagan, J. (author)

Published in:

Geotechnical and Geological Engineering ; 34

Publication date:

2015

ISSN:

DOI:

https://doi.org/10.1007/s10706-015-9967-4

Type of media:

Article (Journal)

Type of material:

Print

Language:

English

Keywords:

Generalized regression neural network , Gaussian process regression , Quick sand , First order reliability method , Multivariate adaptive regression spline

Classification:

BKL: 38.58 Geomechanik / 57.00 Bergbau: Allgemeines / 56.20 Ingenieurgeologie, Bodenmechanik
Local classification TIB: 275/3750

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