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Shear capacity prediction of FRP-RC beams using single and ensenble ExPlainable Machine learning models
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting
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SVM Tutorial — Classification, Regression and Ranking
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Effect of FRP bar degradation on interface bond with high strength concrete
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Shear behavior of green concrete beams reinforced with basalt FRP bars and stirrups
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Flexural and shear capacities of concrete beams reinforced with GFRP bars
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Prediction of elastic modulus of normal and high strength concrete by artificial neural networks
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Prediction of compressive strength of concrete containing construction and demolition waste using artificial neural networks
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Machine learning prediction of mechanical properties of concrete: Critical review
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Machine learning prediction of compressive strength for phase change materials integrated cementitious composites
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Rapid seismic damage evaluation of bridge portfolios using machine learning techniques
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Data-driven machine-learning-based seismic failure mode identification of reinforced concrete shear walls
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Implementing ensemble learning methods to predict the shear strength of RC deep beams with/without web reinforcements
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Development of extreme gradient boosting model for prediction of punching shear resistance of r/c interior slabs
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Shear behavior of basalt FRC beams reinforced with basalt FRP bars and glass FRP stirrups: Experimental and analytical investigations
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Plastic hinge length of rectangular RC columns using ensemble machine learning model
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Explainable extreme gradient boosting tree-based prediction of load-carrying capacity of FRP-RC columns
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Machine learning-based approaches for seismic demand and collapse of ductile reinforced concrete building frames
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Influence of Longitudinal GFRP Reinforcement Ratio on Shear Capacity of Concrete Beams without Stirrups
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Prediction of shear strength of reinforced concrete beams using adaptive neuro-fuzzy inference system and artificial neural network
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Classification and Regression Trees, Bagging, and Boosting
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Flexural behaviour of concrete beams reinforced with GFRP bars
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Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling
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Shear Strength of Normal Strength Concrete Beams Reinforced with Deformed GFRP Bars
inferredcites →https://doi.org/10.1061/(asce)1090-0268(2004)8:5(452)openalex-snapshot
Concrete Contribution to the Shear Resistance of Fiber Reinforced Polymer Reinforced Concrete Members
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Shear Strength of One-Way Concrete Slabs Reinforced with Fiber-Reinforced Polymer Composite Bars
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Shear Resistance of FRP RC Beams: Experimental Study
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Shear Performance of RC Bridge Girders Reinforced with Carbon FRP Stirrups
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Shear Strength of Large Concrete Members with FRP Reinforcement
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Shear Strength of Fiber-Reinforced Polymer Reinforced Concrete Beams Subject to Unsymmetric Loading
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Shear Behavior of FRP-Reinforced Concrete Deep Beams without Web Reinforcement
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Concrete Shear Strength of Normal and Lightweight Concrete Beams Reinforced with FRP Bars
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Shear Strength of FRP Reinforced Concrete Members with Stirrups
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Performance of Concrete Beams Reinforced with Basalt FRP for Flexure and Shear
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Shear Behavior of Basalt Fiber Reinforced Concrete Beams with and without Basalt FRP Stirrups
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Concrete Contribution to Shear Strength of Beams Reinforced with Basalt Fiber-Reinforced Bars
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Shear Strength Prediction in Reinforced Concrete Deep Beams Using Nature-Inspired Metaheuristic Support Vector Regression
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Shear Strength of Normal and High Strength Concrete Beams Reinforced with GFRP Bars
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Guide for the Design and Construction of Concrete Reinforced with FRP Bars (ACI 440.1R-03)
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Flexural Behaviour of Concrete Beams Reinforced With GFRP Bars
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On the Shear Behaviour of Concrete Beams Reinforced by Carbon Fibre‐Reinforced Polymer Bars: An Experimental Investigation by Means of Acoustic Emission Technique
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Fibre reinforced polymer shear reinforcement for concrete members: behaviour and design guidelines
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Shear strength of fibre-reinforced polymer reinforced concrete deep beams without web reinforcement
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Classifying earthquake damage to buildings using machine learning
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The International Handbook of FRP Composites in Civil Engineering
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Shear Tests of FRP-Reinforced Concrete Beams without Stirrups
inferredcites →https://doi.org/10.14359/12802openalex-snapshot
Concrete Shear Strength: Another Perspective
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Shear Strength of FRP-Reinforced Concrete Beams without Transverse Reinforcement
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Shear Capacity of High-Strength Concrete Beams Reinforced with Fiber-Reinforced Polymer Bars
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Shear Capacity of RC and PC Beams Using FRP Reinforcement
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Shear Performance of Concrete Beams Reinforced With FRP Stirrups
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Behavior of Concrete Deep Beams Reinforced with Internal Fiber-Reinforced Polymer—Experimental Study
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Size Effect on Concrete Shear Strength in Beams Reinforced with Fiber-Reinforced Polymer Bars
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Experimental Investigation of Glass Fiber-Reinforced Polymer-Reinforced Normal-Strength Concrete Beams
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One-Way Slabs Reinforced with Glass Fiber Reinforced Polymer Reinforcing Bars
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EVALUATION OF SHEAR STRENGTH OF CONCRETE BEAMS REINFORCED WITH FRP
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SHEAR CAPACITY OF CONCRETE BEAMS USING FRP REINFORCEMENT
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Consistent Individualized Feature Attribution for Tree Ensembles
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Solubilization of inclusion bodies: insights from explainable machine learning approaches
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Torsional Capacity Prediction of Reinforced Concrete Beams Using Machine Learning Techniques Based on Ensembles of Trees
inferred← citeshttps://doi.org/10.3390/app13179906openalex-snapshot
High-Speed Motion Analysis-Based Machine Learning Models for Prediction and Simulation of Flyrock in Surface Mines
inferred← citeshttps://doi.org/10.3390/asi8040096openalex-snapshot
Shear Strength Prediction for RCDBs Utilizing Data-Driven Machine Learning Approach: Enhanced CatBoost with SHAP and PDPs Analyses
inferred← citeshttps://doi.org/10.3390/buildings12111895openalex-snapshot
Mechanical Behavior of Special-Shaped Reinforced Concrete Composite Columns Encased with GFRP Core Columns
inferred← citeshttps://doi.org/10.3390/buildings13020313openalex-snapshot
Data-Driven Shear Strength Prediction of FRP-Reinforced Concrete Beams without Stirrups Based on Machine Learning Methods
inferred← citeshttps://doi.org/10.3390/buildings13061395openalex-snapshot
Shear Capacity Prediction Model of Deep Beam Based on New Hybrid Intelligent Algorithm
inferred← citeshttps://doi.org/10.3390/buildings13102528openalex-snapshot
Unbonded Pre-Tensioned CF-Laminates Mechanically Anchored to HSC Beams as a Sustainable Repair Solution for Detachment of Bonded CF-Laminates
inferred← citeshttps://doi.org/10.3390/buildings14072080openalex-snapshot
Interpretable Machine Learning Models for Prediction of UHPC Creep Behavior
inferred← citeshttps://doi.org/10.3390/buildings16173545openalex-snapshot
Interpretable Machine Learning for Predicting Compressive Strength of CFRP-Confined UHPC Short Columns
inferred← citeshttps://doi.org/10.3390/ma16114034openalex-snapshot
Metaheuristic Optimization of Random Forest for Predicting Punch Shear Strength of FRP-Reinforced Concrete Beams
inferred← citeshttps://doi.org/10.3390/ma16155381openalex-snapshot
Explainable Artificial Intelligence to Investigate the Contribution of Design Variables to the Static Characteristics of Bistable Composite Laminates
inferred← citeshttps://doi.org/10.3390/make8060160openalex-snapshot
Interpretable Machine Learning for the Shear Capacity of RC Corbels: A Validated, Application-Driven Model
inferred← citeshttps://doi.org/10.3390/polym15132857openalex-snapshot
Investigation of the Shear Behavior of Concrete Beams Reinforced with FRP Rebars and Stirrups Using ANN Hybridized with Genetic Algorithm
inferred← citeshttps://doi.org/10.3390/polym18202503openalex-snapshot
Material-Efficient Selection of Externally Bonded Fiber-Reinforced Polymer Composites for RC Shear Strengthening Using a Literature-Based Database and Break-Even Criteria
inferred← citeshttps://doi.org/10.3390/pr13103053openalex-snapshot
Fire Resistance Prediction in FRP-Strengthened Structural Elements: Application of Advanced Modeling and Data Augmentation Techniques
inferred← citeshttps://doi.org/10.3390/s25216649openalex-snapshot
eXplainable Artificial Intelligence (XAI): A Systematic Review for Unveiling the Black Box Models and Their Relevance to Biomedical Imaging and Sensing
inferred← citeshttps://doi.org/10.3390/su15042892openalex-snapshot
Using Artificial Intelligence Approach for Investigating and Predicting Yield Stress of Cemented Paste Backfill
inferred← citeshttps://doi.org/10.3390/su16010011openalex-snapshot
The Efficiency of Using Machine Learning Techniques in Fiber-Reinforced-Polymer Applications in Structural Engineering
inferred← citeshttps://doi.org/10.59382/j-ibst.2025.vi.vol3-3openalex-snapshot
Deep learning model for predicting moment capacity of composite beam utilizing HSS girder and ECC slab
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