The hydro-mechanical behavior of a material is an imminent criterion for assessing the
performance of a liner and sub-base material. Several materials have been explored in the …

The present research employs new boosting-based ensemble machine learning models ie,
gradient boosting (GB) and adaptive boosting (AdaBoost) to predict the unconfined …

To optimize the workflow of civil engineering construction in a harbour, this paper developed
a framework of the contaminant leaching assessment carried out on the stabilized/solidified …

In this study, we compared the Ultimate Bearing Capacity (UBC) of shallow foundations on
sandy soils that were predicted using Analytical, Finite Element Modeling (FEM), and …

Diatomaceous soils, composed of diatom microfossils with biological origins, have
geotechnical properties that are fundamentally different from those of conventional non …

This research paper presents a comprehensive study on optimizing the critical artificial
intelligence (AI) factors influencing cost management in civil engineering projects using a …

This study explores the application of machine learning (ML) for predicting the optimum
moisture content (OMC) of soil–stabilizer mixtures. The study utilizes support vector …

Tunneling, especially in urban areas, affects many structures on the ground, which directly
influences the usability and stability of the structures. The settlement of and axial stress on …

Accurate mapping plays a crucial role in the management of natural hazards, particularly in
the monitoring of sand dune movement. In this research, we focused on modeling sand …

Electric energy demand forecasting is vital in contemporary power systems, especially
amidst market deregulation trends and the increasing influence of industrial customers on …