Explainable Hybridized Machine Learning for Prediction of Compressive Strength of Fly-Ash based Geopolymer Concrete

Hybrid Artificial Neural Network Models for Predicting Flexural Strength of FRP-Reinforced Concrete Beams

An Efficient Meta-Ensemble Paradigm for Modelling Poisson’s Ratio and Maximum Horizontal Stress in Casing Collapse Hazard

Explainable Predictive Modelling of Sustainable Slag–Fly Ash Based Geopolymer Concrete with Life Cycle and Carbon-Neutrality Assessment

Dynamic Response of SDoF System with Negative Stiffness—A Relevant Key-Point for Machine Learning

Prediction of Chloride Resistance Level in Concrete Using Optimized Tree-Based Machine Learning Models

Intelligent Data Driven Ensemble Approaches for Bending Strength Prediction of Ultra-High Performance Concrete Beams