THERMAL SCIENCE

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Ahmet Haşim Yurttakal

EXTREME GRADIENT BOOSTING REGRESSION MODEL FOR SOIL THERMAL CONDUCTIVITY

ABSTRACT
The thermal conductivity estimation for the soil is an important step for many geothermal applications. But it is a difficult and complicated process since it involves a variety of factors that have significant effects on the thermal conductivity of soils such as soil moisture and granular structure. In this study, regression was performed with the extreme gradient boosting algorithm to develop a model for estimating thermal conductivity value. The performance of the model was measured on the unseen test data. As a result, the proposed algorithm reached 0.18 RMSE, 0.99 R2, and 3.18% MAE values which state that the algorithm is encouraging.
KEYWORDS
Gradient Boosting, thermal conductivity, regression
PAPER SUBMITTED: 2020-06-12
PAPER REVISED: 2020-11-11
PAPER ACCEPTED: 2020-11-15
PUBLISHED ONLINE: 2021-01-24
DOI REFERENCE: https://doi.org/10.2298/TSCI200612001Y
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2021, VOLUME 25, ISSUE Special issue 1, PAGES [1 - 7]
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Extreme gradient boosting regression model for soil thermal conductivity

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence