A machine learning approach for mapping the very shallow theoretical geothermal potential

Dan Assouline, Nahid Mohajeri, Agust Gudmundsson, Jean-Louis Scartezzini

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@article{b89a2e6ae0c74183828cb7f2b2c00c38,

title = "A machine learning approach for mapping the very shallow theoretical geothermal potential",

author = "Dan Assouline and Nahid Mohajeri and Agust Gudmundsson and Jean-Louis Scartezzini",

year = "2019",

month = jul,

day = "25",

doi = "10.1186/s40517-019-0135-6",

language = "English",

volume = "7",

pages = "1--50",

journal = "Geothermal Energy",

publisher = "Springer Nature",

}

TY - JOUR

T1 - A machine learning approach for mapping the very shallow theoretical geothermal potential

AU - Assouline, Dan

AU - Mohajeri, Nahid

AU - Gudmundsson, Agust

AU - Scartezzini, Jean-Louis

PY - 2019/7/25

Y1 - 2019/7/25

U2 - 10.1186/s40517-019-0135-6

DO - 10.1186/s40517-019-0135-6

M3 - Article

VL - 7

SP - 1

EP - 50

JO - Geothermal Energy

JF - Geothermal Energy

M1 - 19

ER -