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

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 …

In this study, a model for the estimation of the compressive strength of concretes
incorporating metakaolin is developed and parametrically evaluated, using soft computing …

The application of the traditional support vector regression (SVR) model to predict the
compressive strength of concrete faces the challenge of parameter tuning. To this end, a …

Foamed concrete is special not only in terms of its unique properties, but also in terms of its
challenging compositional mixture design, which necessitates multiple experimental trials …

Basalt fiber is a green non-polluting material with strong tensile mechanical properties. In
this paper, the strength prediction model of basalt fiber concrete is constructed by random …

Recycled agricultural wastes are being used in the building and construction sector as
cement additives as a result of the environmental impact of cement production. Agricultural …

Maximising the content of supplementary cementitious materials as a partial replacement for
Portland cement and using recycled concrete aggregates as a full or partial replacement for …

This study investigated the importance of applying explainable artificial intelligence (XAI) on
different machine learning (ML) models developed to predict the strength characteristics of …

Abstract Recently, hydrogen (H 2) gas has gained prodigious attention as a sustainable
energy carrier to reduce acute dependence on fossil fuels due to its fascinating properties …