This study presents a comprehensive review of the Land subsidence (LS) cases, as a
worldwide environmental, geological, and global geohazard concern. Here, 290 case …

Abstract Machine learning (ML) may provide a new methodology to directly learn from raw
data to develop constitutive models for soils by using pure mathematic skills. It has …

Metro system is a vital component of mass transportation infrastructure, providing crucial
social and economic service in urban area. Flood events may cause functional disruptions to …

This study presents an improved trapezoidal fuzzy analytic hierarchy process (FAHP) to
assess the risk of mega-city infrastructures related to land subsidence. The trapezoidal fuzzy …

A comparative study of optimization techniques for identifying soil parameters in
geotechnical engineering was first presented. The identification methodology with its 3 main …

The existing longitudinal structural model of shield tunnels usually simplify the tunnel as a
Euler-Bernoulli beam on elastic foundation, which ignores the shearing dislocation between …

Soft structured clays usually exhibit complex behaviors, which can lead to difficulties in the
determination of parameters and high testing costs. This paper aims to propose an efficient …

Compression index C c is an essential parameter in geotechnical design for which the
effectiveness of correlation is still a challenge. This paper suggests a novel modelling …

Coupled hydromechanical finite-element modeling of granular soils, taking into account
internal erosion, is computationally prohibitive. Alternative data-driven approaches require …

There is significant potential for machine learning (ML) to achieve step-change advances in
the state-of-the-art for constitutive modelling of geomaterials. However, a common challenge …