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 …

In an age of depleting earth due to global warming impacting badly on the ozone layer of the
earth system, the need to employ technologies to substitute those engineering practices …

Most of the existing machine learning (ML)-based models for liquefaction assessment of
soils are black-box in nature. Database considered in the existing studies for model …

This study presents a cleaner production of a concrete by incorporating waste rubber chips
and pozzolans to make a greener concrete through partial replacement of aggregates and …

Soft soils pose significant challenges to the environment and construction of infrastructure
on them owing to their distinct characteristics such as low bearing strength, high water …

Majority of the presently available machine learning (ML) models employed to assess the
liquefaction potential of soils are for sands or sands containing silt fraction. In the current …

Mineral prospectivity mapping (MPM) is a fundamental task in mineral exploration. The
logistic regression (LR) method has been widely used as a data-driven tool for MPM …

Due to their inherent natural properties, the basic physio-mechanical properties of geo-
materials generally exhibit varying degrees of spatial variability. Therefore, describing and …

This study aims to propose a novel and high-accuracy prediction model of plastic limit (PL)
based on soil particles passing through sieve# 200 (0.075 mm) using gene expression …

Seismically induced soil liquefaction has been documented after the M7. 8, 2016
Pedernales earthquake. In the city of Jama, the acceleration recorded by soil amplification …