The primary challenges in metropolitan planning, selection of sites, and develo**
preemptive safety measures lie in the characterization and precise appraisal of underground …

The evaluation of ultimate bearing capacity (Qu) of rock socketed shafts (RSSs) is crucial for
the design of foundation systems. This study proposes a new data-driven multivariate …

This study employs spatial interpolation techniques based on extensive geotechnical sub-
soil data to develop geotechnical zonation maps for the district of Sargodha, Pakistan. The …

The substantial spatial variability of subsoil information in small grids poses a significant
challenge for geological and geotechnical experts. In this regard, comprehensive …

To achieve smart and sustainable construction goals, machine learning (ML) techniques can
serve as a cost-effective and efficient substitute for labour-intensive, laboratory, or in situ …

This study developed artificial intelligence models to predict Atterberg's limits, specifically
the liquid (LL) and plastic limits (PL), based on# 200 sieve analysis, which is a laborious and …

Accurate map** of the geotechnical parameters poses a challenge for geotechnical and
geological experts due to the limited level of investigation and inherent spatial variations …

Pile bearing capacity (Pu) is a vital aspect of geotechnical engineering and foundation
design, representing the maximum load a single pile or a group of piles can support without …

This study addresses a critical issue of sample disturbance in predicting the elastic modulus
(E s) of soft cohesive soils using machine learning techniques. Traditional approaches either …

The work focuses on creating a hybrid retaining wall using geocell, geogrid, and soil-nailing
techniques for a road embankment in Mangalore, India. Soil nailing reinforces the soil …