Machine learning-based prediction of tensile strength of glass fiber-reinforced polymer rebar under environmental conditions.
- DOI
- 10.1177/13694332251363357
- Published
- 2026 Apr
- Container
- Advances in structural engineering
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1177/13694332251363357,
title = {Machine learning-based prediction of tensile strength of glass fiber-reinforced polymer rebar under environmental conditions.},
author = {Cheng Y and Geng X and Wu C},
year = {2026},
journal = {Advances in structural engineering},
doi = {10.1177/13694332251363357},
url = {https://doi.org/10.1177/13694332251363357}
}RIS
TY - JOUR TI - Machine learning-based prediction of tensile strength of glass fiber-reinforced polymer rebar under environmental conditions. AU - Cheng Y AU - Geng X AU - Wu C PY - 2026 JO - Advances in structural engineering DO - 10.1177/13694332251363357 UR - https://doi.org/10.1177/13694332251363357 ER -
APA
Y, C., X, G., & C, W. (2026). Machine learning-based prediction of tensile strength of glass fiber-reinforced polymer rebar under environmental conditions.. Advances in structural engineering. https://doi.org/10.1177/13694332251363357
Source records
- pubmed · retrieved 2026-09-25T07:24:26.429Z