... 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...

... structures data-driven deep beams machine learning reinforced concrete shear capacity shear reinforcement a/d shear span to depth ratio b width of beam d effective depth f c ′   compressive strength of concrete...

... 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...