Efficient g-function approximation with artificial neural networks for a varying number of boreholes on a regular or irregular layout

Bernard Dusseault, Philippe Pasquier

Article (2019)

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Department:
Department of Civil, Geological and Mining Engineering
PolyPublie URL:
https://publications.polymtl.ca/43608/
Journal Title :
Science and Technology for the Built Environment ( vol. 25 , no. 8 )
Publisher:
Taylor and Francis Inc.
DOI:
10.1080/23744731.2019.1634932
Official URL:
https://doi.org/10.1080/23744731.2019.1634932
OAI:
oai:publications.polymtl.ca:43608
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Date Deposited:
18 Apr 2023 15:01
Last Modified:
14 Oct 2026 13:55
Cite in APA 7:
Dusseault, B., & Pasquier, P. (2019). Efficient g-function approximation with artificial neural networks for a varying number of boreholes on a regular or irregular layout. Science and Technology for the Built Environment, 25(8), 1023-1035. https://doi.org/10.1080/23744731.2019.1634932

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