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, 3.18% MAE values which
state that the algorithm is encouraging.
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