The non-destructive testing of concrete structures with methods such as ultrasonic pulse
velocity and Schmidt rebound hammer test is of utmost technical importance. Non …

The use of three artificial neural network (ANN)-based models for the prediction of
unconfined compressive strength (UCS) of granite using three non-destructive test …

Purpose This study reviews the extent of application of artificial intelligence (AI) tools in the
construction industry. Design/methodology/approach A thorough literature review (based on …

This paper reports the results of advanced data analysis involving artificial neural networks
for the prediction of the unconfined compressive strength of granite using only two non …

Despite the abundance of research works, both experimental and theoretical, conducted
since the middle of the previous century up to today, the determination of the shear stress …

Despite the extensive use of mortar materials in constructions over the last decades, there is
not yet a robust quantitative method, available in the literature, which can reliably predict …

In recent years, natural hydraulic lime (NHL) mortars have gained increased attention from
researchers, not only as restoration materials for monuments and historical buildings, but …

Numerous studies have reported the effective use of artificial intelligence approaches,
particularly artificial neural networks (ANNs)-based models, to tackle tunnelling issues …

The masonry is not only included among the oldest building materials, but it is also the most
widely used material due to its simple construction and low cost compared to the other …

The present paper discussed the development of a reliable and robust artificial neural
network (ANN) capable of predicting the tribological performance of three highly alloyed tool …