Artificial Neural Networks in Geotechnical Engineering: A State-of-the-Art Review of Soil Characterization and Pile-Foundation Applications

Jamal Al Tahat

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DOI: 10.22541/authorea.15009463/v1
Published: 2026-09-24
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Publisher: Wiley
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Cite this work

BibTeX

@article{allodium:10.22541/authorea.15009463/v1,
  title = {Artificial Neural Networks in Geotechnical Engineering: A State-of-the-Art Review of Soil Characterization and Pile-Foundation Applications},
  author = {Jamal Al Tahat},
  year = {2026},
  doi = {10.22541/authorea.15009463/v1},
  url = {https://doi.org/10.22541/authorea.15009463/v1}
}

RIS

TY  - JOUR
TI  - Artificial Neural Networks in Geotechnical Engineering: A State-of-the-Art Review of Soil Characterization and Pile-Foundation Applications
AU  - Jamal Al Tahat
PY  - 2026
DO  - 10.22541/authorea.15009463/v1
UR  - https://doi.org/10.22541/authorea.15009463/v1
ER  -

APA

Tahat, J. A. (2026). Artificial Neural Networks in Geotechnical Engineering: A State-of-the-Art Review of Soil Characterization and Pile-Foundation Applications. https://doi.org/10.22541/authorea.15009463/v1

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crossref · retrieved 2026-11-10T18:04:48.572Z