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Explainable hybridized ensemble machine learning for the prognosis of the compressive strength of recycled plastic-based sustainable concrete with experimental …
Concrete composed of recycled aggregate has been implemented in the construction of
buildings due to its potential to mitigate concrete pollution, thereby reducing the …
buildings due to its potential to mitigate concrete pollution, thereby reducing the …
[HTML][HTML] Machine-learning-based predictive models for punching shear strength of FRP-reinforced concrete slabs: a comparative study
W Xu, X Shi - Buildings, 2024 - mdpi.com
This study is focused on the punching strength of fiber-reinforced polymer (FRP) concrete
slabs. The mechanical properties of reinforced concrete slabs are often constrained by their …
slabs. The mechanical properties of reinforced concrete slabs are often constrained by their …
Hybrid machine learning model to predict the mechanical properties of ultra-high-performance concrete (UHPC) with experimental validation
Ultra-high-performance concrete (UHPC) incorporating waste cementitious materials has
become widely used due to its extraordinary mechanical strength and durability. Adding …
become widely used due to its extraordinary mechanical strength and durability. Adding …
Explainable prediction model for punching shear strength of FRP-RC slabs based on kernel density estimation and XGBoost
Reinforced concrete (RC) slabs are widely used in modern building structures due to their
superior properties and ease of construction. However, their mechanical properties are …
superior properties and ease of construction. However, their mechanical properties are …
Prediction of split tensile strength of recycled aggregate concrete leveraging explainable hybrid XGB with optimization algorithm
Recycled aggregate concrete (RAC) has been adopted in building construction as it can
reduce concrete waste, eventually minimizing the environmental impact. However, using …
reduce concrete waste, eventually minimizing the environmental impact. However, using …
Prediction of autogenous shrinkage in ultra-high-performance concrete (UHPC) using hybridized machine learning
This study explores hybridized machine learning (ML) techniques to predict autogenous
shrinkage (AS) in ultra-high-performance concrete (UHPC). The ensemble model, namely …
shrinkage (AS) in ultra-high-performance concrete (UHPC). The ensemble model, namely …
[HTML][HTML] Experimental and Transformer-Based Study on Seismic Behavior and Plastic Hinge Length of RC Columns Reinforced with End-Fixed Ultra-High Strength …
The application of machine learning (ML) in structural engineering is receiving increasing
attention recently. This paper experimentally studies three self-restoring reinforced concrete …
attention recently. This paper experimentally studies three self-restoring reinforced concrete …
Optimizing high-strength concrete compressive strength with explainable machine learning
This study leverages machine learning to enhance the prediction of high-strength concrete
(HSC) compressive strength, addressing the limitations of conventional methods, which are …
(HSC) compressive strength, addressing the limitations of conventional methods, which are …
Numerical simulation of post fire-behaviour of high strength lightweight reinforced concrete beams strengthened with basalt fiber-reinforced polymer grid and …
NA Shareef, MM Kadhum - Journal of Building Pathology and …, 2025 - Springer
This study examined a new composite strengthening method using a basalt fiber-reinforced
polymer (BFRP) grid combined with engineered cementitious composites (ECC) matrix to …
polymer (BFRP) grid combined with engineered cementitious composites (ECC) matrix to …