It was 35 years ago since the first usage of Artificial Intelligence (AI) technique in
geotechnical engineering, during those years many (AI) techniques were developed based …

Over the last few years, artificial neural networks (ANNs) have been used successfully for
modeling almost all aspects of geotechnical engineering problems. Whilst ANNs provide a …

The prediction of liquefaction-induced lateral spreading/displacement (D h) is a challenging
task for civil/geotechnical engineers. In this study, a new approach is proposed to predict D h …

This paper presents an artificial neural network (ANN) based mathematical model for the
prediction of blast-induced ground vibrations using the data obtained from the literature. A …

Artificial neural networks (ANNs) are a form of artificial intelligence that has proved to
provide a high level of competency in solving many complex engineering problems that are …

Accurate suspended sediment prediction is an integral component of sustainable water
resources and environmental systems. This study considered artificial neural network (ANN) …

In the last few decades, numerous methods have been developed for predicting the axial
capacity of pile foundations. Among the available methods, the cone penetration test (CPT) …

This study presents a literature review on the use of artificial neural networks in the
prediction of geo-mechanical properties of stabilised clays. In this paper, the application of …

Blast-induced ground vibration is one of the most severe and complex environmental
problems associated with blasting operation. The scaled-distance approach is the common …

Punching shear capacity is an important parameter in designing structural elements.
Accurate estimation of punching shear capacity typically requires rigorous calculation …