Suitability of Mechanics-Based and Optimized Machine Learning-Based Models in the Shear Strength Prediction of Slender Beams Without Stirrups

Suitability of Mechanics-Based and Optimized Machine Learning-Based Models in the Shear Strength Prediction of Slender Beams Without Stirrups

Accurate shear capacity estimation for reinforced concrete (RC) beams without stirrups is essential for reliable structural design. Traditional code-based methods, primarily empirical, exhibit variability in predicting shear strength for these beams. This paper assesses the effectiveness of mechanic...

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Bibliographic Details
Main Authors: Abayomi B. David, Oladimeji B. Olalusi, Paul O. Awoyera, Lenganji Simwanda
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Buildings
Subjects:
beams
shear strength
machine learning
model uncertainty
Shapley additive explanation method
XGBoost algorithm
Online Access:https://www.mdpi.com/2075-5309/14/12/3946
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