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Determination of the Angle of Shearing Resistance of Soils Using Multivariate Adaptive Regression Spline

Samui, Pijush

This article adopts Multivariate Adaptive Regression Spline (MARS) for prediction of Angle of Shearing Resistance(ϕ) of soil. MARS is an adaptive, non-parametric regression approach. Percentages of fine-grained (FG), coarse-grained (CG), liquid limit (LL), and bulk density (BD) have been used as input variables of MARS. The developed MARS gives an equation for prediction of ϕ of soil. The results of MARS have been compared with Genetic Expression Programming (GEP), Artificial Neural Network (ANN), and Adaptive Neuro Fuzzy Inference System (ANFIS) models. These results demonstrate that the developed MARS can be used as a robust model for determination of ϕ of soil.

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Determination of the Angle of Shearing Resistance of Soils Using Multivariate Adaptive Regression Spline

Samui, Pijush

This article adopts Multivariate Adaptive Regression Spline (MARS) for prediction of Angle of Shearing Resistance(ϕ) of soil. MARS is an adaptive, non-parametric regression approach. Percentages of fine-grained (FG), coarse-grained (CG), liquid limit (LL), and bulk density (BD) have been used as input variables of MARS. The developed MARS gives an equation for prediction of ϕ of soil. The results of MARS have been compared with Genetic Expression Programming (GEP), Artificial Neural Network (ANN), and Adaptive Neuro Fuzzy Inference System (ANFIS) models. These results demonstrate that the developed MARS can be used as a robust model for determination of ϕ of soil.

Determination of the Angle of Shearing Resistance of Soils Using Multivariate Adaptive Regression Spline

Samui, Pijush

This article adopts Multivariate Adaptive Regression Spline (MARS) for prediction of Angle of Shearing Resistance(ϕ) of soil. MARS is an adaptive, non-parametric regression approach. Percentages of fine-grained (FG), coarse-grained (CG), liquid limit (LL), and bulk density (BD) have been used as input variables of MARS. The developed MARS gives an equation for prediction of ϕ of soil. The results of MARS have been compared with Genetic Expression Programming (GEP), Artificial Neural Network (ANN), and Adaptive Neuro Fuzzy Inference System (ANFIS) models. These results demonstrate that the developed MARS can be used as a robust model for determination of ϕ of soil.

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Title:

Determination of the Angle of Shearing Resistance of Soils Using Multivariate Adaptive Regression Spline

Contributors:

Samui, Pijush (author) / Kim, Dookie

Published in:

Marine georesources & geotechnology ; 33

Publication date:

2015

ISSN:

DOI:

https://doi.org/10.1080/1064119X.2014.954655

Type of media:

Article (Journal)

Type of material:

Print

Language:

English

Keywords:

Mineralischer Rohstoff , Meer , Zeitschrift

Classification:

Local classification TIB: 275/3750
BKL: 56.20 Ingenieurgeologie, Bodenmechanik / 38.48 Marine Geologie / 57.14 Meeresbergbau

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