Prediction of Poisson’s ratio for a petroleum engineering application: Machine learning methods
- DOI
- 10.1371/journal.pone.0317754
- Published
- 2025-02-21
- Container
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1371/journal.pone.0317754,
title = {Prediction of Poisson’s ratio for a petroleum engineering application: Machine learning methods},
author = {Fahd Saeed Alakbari and Syed Mohammad Mahmood and Mohammed Abdalla Ayoub and Muhammad Jawad Khan and Funsho Afolabi and Mysara Eissa Mohyaldinn and Ali Samer Muhsan},
year = {2025},
journal = {PLOS ONE},
doi = {10.1371/journal.pone.0317754},
url = {https://doi.org/10.1371/journal.pone.0317754}
}RIS
TY - JOUR TI - Prediction of Poisson’s ratio for a petroleum engineering application: Machine learning methods AU - Fahd Saeed Alakbari AU - Syed Mohammad Mahmood AU - Mohammed Abdalla Ayoub AU - Muhammad Jawad Khan AU - Funsho Afolabi AU - Mysara Eissa Mohyaldinn AU - Ali Samer Muhsan PY - 2025 JO - PLOS ONE DO - 10.1371/journal.pone.0317754 UR - https://doi.org/10.1371/journal.pone.0317754 ER -
APA
Alakbari, F. S., Mahmood, S. M., Ayoub, M. A., Khan, M. J., Afolabi, F., Mohyaldinn, M. E., & Muhsan, A. S. (2025). Prediction of Poisson’s ratio for a petroleum engineering application: Machine learning methods. PLOS ONE. https://doi.org/10.1371/journal.pone.0317754
Source records
- crossref · retrieved 2026-09-25T07:22:13.266Z