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

Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging
techniques capable of delivering elegant and affordable solutions which can surpass those …

Artificial intelligence (AI) and Machine learning (ML) train machines to achieve a high level
of cognition and perform human-like analysis. Both AI and ML seemingly fit into our daily …

Fiber-reinforced concrete (FRC) is extensively used in diverse structural engineering
applications, and its mechanical properties are crucial for designing and evaluating its …

Natural fibers are eco-friendly, cost-effective, lightweight, renewable, have better thermal
properties and corrosion resistance capabilities. The addition of natural fibers in …

The recent boom in the construction sector, either for building new infrastructures or for
retrofitting and strengthening of old structures, has placed a great demand for conventional …

Biodiesel has appeared as a renewable and clean energy resource and a means of
diminishing global warming. This study provides Bayesian optimization algorithm (BOA) …

In this study, the mechanical properties of glass fiber mortars have been predicted using
machine learning tools, Response Surface Methodology (RSM), and Artificial Neural …

Accurate prediction of the shear capacity of reinforced concrete shear walls (RCSW) is
essential for the wind and seismic design of buildings. However, due to the diverse structural …

The use of fiber-reinforced polymer (FRP) rebars in lieu of steel rebars has led to some
deviations in the shear behavior of concrete members. Several methods have been …