... capacity ( V total ) of FRP-retrofitted RC beams using exploratory data analysis and ensemble machine learning ( ML ) approaches. A comprehensive experimental database comprising rectangular and T-beam specimens was compiled, incorporating geometric properties, material characteristics...

... results and 192 direct tensile test results were gathered to establish four base machine learning models (a decision tree, a random forest, an artificial neural network and extreme gradient boosting). Subsequently, super learner models (SLMs) were constructed to enhance predictive capability...

... of RC members. 26 01 2025 30 12 2025 artificial intelligence beams & girders concrete structures data-driven deep beams machine learning reinforced concrete shear capacity shear reinforcement a/d shear span to depth ratio b...

... the consumption of natural sand. To better predict the residual mechanical properties of concrete after freeze–thaw (F–T) cycles, this study develops four machine learning models: back-propagation neural network, convolutional neural network, decision tree and CatBoost. The input variables were water/cement ratio...