Geotechnical engineering deals with soils and rocks and their use in engineering
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …

The proliferation of data collected by modern tunnel-boring machines (TBMs) presents a
substantial opportunity for the application of machine learning (ML) to support the decision …

Accurate prediction of shield tunneling-induced settlement is a complex problem that
requires consideration of many influential parameters. Recent studies reveal that machine …

Abstract Machine learning (ML) algorithms have been gradually used in predicting tunneling-
induced settlement, but there is no uniform process for establishing ML models and even …

This paper describes the prediction of settlements induced by urban area tunneling using
five machine learning (ML) algorithms. The settlement database, which was collected from a …

Tunnel deformation is closely related to construction safety and requires some specialists to
monitor it for an extended period. So, seeking a timely and convenient method to assess the …

Long-term settlement issues in engineering practice are controlled by the creep index, C α,
but current empirical models of C α are not sufficiently reliable. In a departure from previous …

In order to avoid damage during shield tunnel construction to adjacent buildings on the
ground, it is of paramount importance to precisely predict the Maximum Surface Settlement …

The interaction between a shield machine and the ground is a complicated problem
involving numerous extrinsic and intrinsic factors. Machine learning (ML) algorithms have …

A commonly-encountered problem in foundation design is the reliable prediction of the pile
bearing capacity (PBC). This study is planned to propose a feasible soft computing …