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Cross-database validation and calibrated uncertainty for machine learning models of the shear capacity of FRP-strengthened RC beams Cover

Cross-database validation and calibrated uncertainty for machine learning models of the shear capacity of FRP-strengthened RC beams

Civil and Environmental Engineering
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Open Access
|Oct 2026
Authors

Authors

Sajjad E. Rasheed

sajjad.e@uokerbala.edu.iq

Civil Engineering Department, University of Karbala, Karbala, Iraq

Hasan A. Zainy

Civil Engineer, General Secretariat of the Holy Imam Hussain Shrine, Karbala, Iraq
DOI: https://doi.org/10.2478/cee-2027-0026 | Journal eISSN: 2199-6512 (formerly 1336-5835) | Journal ISSN: 1336-5835
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Language: English
Submitted on: Aug 6, 2026
Accepted on: Sep 2, 2026
Published on: Oct 17, 2026
Published by: University of Žilina
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
FRP shear strengthening,
Machine learning,
Cross-database validation,
Data leakage,
Hierarchical Bayesian model,
Predictive uncertainty
Related subjects:
Business and economics,
Business management,
Industries,
Environmental management

© 2026 Sajjad E. Rasheed, Hasan A. Zainy, published by University of Žilina
This work is licensed under the Creative Commons Attribution 4.0 License.

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