ArticleMaterials (Basel, Switzerland)2023
Interpretable Predictive Modelling of Basalt Fiber Reinforced Concrete Splitting Tensile Strength Using Ensemble Machine Learning Methods and SHAP Approach.
Article in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed.
- Multi-Objective Optimization and Prediction of Mechanical Properties of Green Basalt Fiber-Reinforced Concrete Using Evolutionary ML Algorithms.Materials (Basel, Switzerland) · 2026Article
- Dynamic Ensemble Learning with Transfer Learning for Fatigue Performance Prediction in Ni-Based Superalloys.Materials (Basel, Switzerland) · 2026Article
- A Machine Learning Framework for the Reconstruction of Composite Fatigue and Fracture Properties: A Synthetic Data Study.Materials (Basel, Switzerland) · 2026Article
- Machine learning models for mechanical properties prediction of basalt fiber-reinforced concrete incorporating graphical user interface.Scientific reports · 2025Article
- Predicting the strengths of basalt fiber reinforced concrete mixed with fly ash using AML and Hoffman and Gardener techniques.Scientific reports · 2025Article
- Soft-computing models for predicting plastic viscosity and interface yield stress of fresh concrete.Scientific reports · 2025Article
- Vegetable Fibers in Cement Composites: A Bibliometric Analysis, Current Status, and Future Outlooks.Materials (Basel, Switzerland) · 2025Review
- Predicting mechanical properties of CFRP composites using data-driven models with comparative analysis.PloS one · 2025Article
- A robust LightGBM model for concrete tensile strength forecast to aid in resilience-based structure strategies.Heliyon · 2024Article
- Article
- Prediction of Post-Treatment Visual Acuity in Age-Related Macular Degeneration Patients With an Interpretable Machine Learning Method.Translational vision science & technology · 2024Article
- Theoretical Investigation on Indirect Tensile Strength of Concrete with Rectangular Cross-Section under Locally Distributed Load.Materials (Basel, Switzerland) · 2023Article
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4 authors.
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Abstract
Basalt fibers are a type of reinforcing fiber that can be added to concrete to improve its strength, durability, resistance to cracking, and overall performance. The addition of basalt fibers with high tensile strength has a particularly favorable impact on the splitting tensile strength of concrete. The current study presents a data set of experimental results of splitting tests curated from the literature. Some of the best-performing ensemble learning techniques such as Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Random Forest, and Categorical Boosting (CatBoost) have been applied to the prediction of the splitting tensile strength of concrete reinforced with basalt fibers. State-of-the-art performance metrics such as the root mean squared error, mean absolute error and the coefficient of determination have been used for measuring the accuracy of the prediction. The impact of each input feature on the model prediction has been visualized using the Shapley Additive Explanations (SHAP) algorithm and individual conditional expectation (ICE) plots. A coefficient of determination greater than 0.9 could be achieved by the XGBoost algorithm in the prediction of the splitting tensile strength.
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