Multivariate prediction model of geothermal parameters based on machine learning

Shuang-Fei Zheng, Xu Li and Meng Wang

Energy, 2025, vol. 316, issue C

Abstract: The geothermal parameters (GTPs, C and λ) are fundamental for characterizing heat storage and conduction in the soil. The measurement for these parameters requires complex mathematical models and stringent conditions. This leads to complicated measuring equipment and high time costs.

Keywords: Heat pulse probe; Back analysis; Geothermal parameters; Monte Carlo simulation; Machine learning (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:316:y:2025:i:c:s0360544225001392

DOI: 10.1016/j.energy.2025.134497

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