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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Vydáno v:	Multiscale and Multidisciplinary Modeling, Experiments and Design Ročník 6; číslo 2; s. 199 - 222
Hlavní autoři:	Khatti, Jitendra, Grover, Kamaldeep Singh
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.06.2023
Témata:	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
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