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Geotechnical and Geological Engineering
Erschienen in: Geotechnical and Geological Engineering 1/2014

01.02.2014 | Original paper

Utilization of Gaussian Process Regression for Determination of Soil Electrical Resistivity

verfasst von: Pijush Samui

Erschienen in: Geotechnical and Geological Engineering | Ausgabe 1/2014

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Abstract

Soil electrical resistivity (RE) is an important parameter for geotechnical engineering projects. This article employs Gaussian process regression (GPR) for prediction of RE of soil based on soil thermal resistivity (RT), percentage sum of the gravel and sand size fractions (F), and degree of saturation (Sr). GPR is derived from the perspective of Bayesian nonparametric regression. Two models (Model I and Model II) have been developed. The developed GPR has been compared with the artificial neural network. It gives the variance of the predicted RE. The results show the developed GPR is an efficient tool for prediction of RE of soil.
Vorheriger Artikel Risk Factor Based Design of Cantilever Retaining Walls
Nächster Artikel Effect of Edge Distance from the Slope Crest on the Response of a Laterally Loaded Pile in Sloping Ground

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Metadaten
Titel
Utilization of Gaussian Process Regression for Determination of Soil Electrical Resistivity
verfasst von
Pijush Samui
Publikationsdatum
01.02.2014
Verlag
Springer International Publishing
Erschienen in
Geotechnical and Geological Engineering / Ausgabe 1/2014
Print ISSN: 0960-3182
Elektronische ISSN: 1573-1529
DOI
https://doi.org/10.1007/s10706-013-9705-8

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