Prediction of UCS of fine-grained soil based on machine learning part 1: multivariable regression analysis, gaussian process regression, and gene expression programming

The present research introduces the best architecture approach and model for predicting the unconfined compressive strength (UCS) of cohesive virgin soil by comparing the multivariable regression analysis (MRA), gaussian process regression (GPR), and gene expression programming (GEP) approaches. The...

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Bibliographic Details

Published in:	Multiscale and Multidisciplinary Modeling, Experiments and Design Vol. 6; no. 2; pp. 199 - 222
Main Authors:	Khatti, Jitendra, Grover, Kamaldeep Singh
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 01.06.2023
Subjects:	Characterization and Evaluation of Materials Engineering Mathematical Applications in the Physical Sciences Mechanical Engineering Numerical and Computational Physics Original Paper Simulation Solid Mechanics Gaussian process regression Regression analysis Unconfined compressive strength Machine learning Gene expression programming
ISSN:	2520-8160, 2520-8179
Online Access:	Get full text
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