Prediction of Ultimate Bearing Capacity of Shallow Foundations on Cohesionless Soils: A Gaussian Process Regression Approach

Prediction of Ultimate Bearing Capacity of Shallow Foundations on Cohesionless Soils: A Gaussian Process Regression Approach

This study examines the potential of the soft computing technique—namely, Gaussian process regression (GPR), to predict the ultimate bearing capacity (UBC) of cohesionless soils beneath shallow foundations. The inputs of the model are width of footing (<i>B</i>), depth of footing (<i&...

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Bibliographic Details
Main Authors: Mahmood Ahmad, Feezan Ahmad, Piotr Wróblewski, Ramez A. Al-Mansob, Piotr Olczak, Paweł Kamiński, Muhammad Safdar, Partab Rai
Format: article
Language:EN
Published: MDPI AG 2021
Subjects:
cohesionless soil
machine learning
Gaussian process regression
shallow foundation
ultimate bearing capacity
Technology
T
Engineering (General). Civil engineering (General)
TA1-2040
Biology (General)
QH301-705.5
Physics
QC1-999
Chemistry
QD1-999
Online Access:https://doaj.org/article/9500e13ff9ec412f982811748e6838e8
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https://doaj.org/article/9500e13ff9ec412f982811748e6838e8

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