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A B S T R A C T This study explores and validates a machine learning approach for the practical, effective, and precise prediction of the thermo-physical characteristics that are essential for the analysis and design of shallow geothermal systems, including borehole heat exchangers: (i) undisturbed ground temperature, (ii) ground effective thermal conductivity, and (iii) borehole thermal resistance. Benefiting from 174 thermal response tests from central and western Switzerland, the algorithmdoi:10.1016/j.geothermics.2021.102132 fatcat:yjdgghz3afbhfg6mope34pfkty