In this research, we present an efficient implementation of machine learning (ML) models
that forecast the mechanical properties of basalt fiber-reinforced high-performance concrete …

Ensemble learning (EL) has gained popularity in recent investigations because of its higher
prediction accuracy than conventional machine learning (ML) methods. Regressors and EL …

Continuous research efforts have been developed in the literature to raise the sustainability
components of the road infrastructure industry, ie, reduce potential contaminants and …

Recycled aggregate concrete (RAC) not only alleviates the shortage of natural aggregates
but also promotes the recycling of construction and demolition waste, contributing to …

Recycled aggregate concrete (RAC) has become a popular building material due to its eco-
friendly features, but the difficulty in predicting the crack resistance of RAC is increasingly …

The demand for concrete production has led to a significant annual requirement for raw
materials, resulting in a substantial amount of waste concrete. In response, recycled …

The effect of various parameters on the flexural strength (FS) of ultra-high-performance
concrete (UHPC) is an intricate mechanism due to the involvement of several inter …

A concise general equation is difficult to reflect the relationship between physical properties
of conductive materials and properties of conductive mortar (CM). To handle this issue, a …

The use of ensemble learning (EL) has grown due to its ability to enhance precision in
predictions compared to typical machine learning (ML) algorithms. EL-based approaches …

The construction industry is shifting towards sustainability, emphasizing the need for
innovative materials. Recycled Aggregate Concrete (RAC), utilizing recycled aggregates …