Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …

Concrete is one of the most widely used materials in various civil engineering applications.
Its global production rate is increasing to meet demand. Mechanical properties of concrete …

Concrete, as the most widely used construction material, is inextricably connected with
human development. Despite conceptual and methodological progress in concrete science …

Abstract Machine learning (ML) techniques are often employed for the accurate prediction of
the compressive strength of concrete. Despite higher accuracy, previous ML models failed to …

Accurate prediction of the mechanical properties of concrete has been a concern since
these properties are often required by design codes. The emergence of new concrete …

The compressive strength of fiber-reinforced rubberized recycled aggregate concrete (FR 3
C) is an important performance indicator for its practical application and durability in the …

This study aims to apply machine learning methods to predict the compression strength of
self-compacting recycled aggregate concrete. To obtain this goal, the ensemble methods …

In this study, four machine learning (ML) algorithms, namely Support Vector Machine (SVM),
Back-propagation Artificial Neural Network (BP-ANN), Adaptive Boosting (AdaBoost), and …

A crucial factor in the efficient design of concrete sustainable buildings is the compressive
strength (Cs) of eco-friendly concrete. In this work, a hybrid model of Gradient Boosting …

The mixture proportioning of conventional concrete is commonly established using
regression analysis of experimental data. However, such traditional empirical procedures …