Owing to recent advancements in sensor technology, data mining, Machine Learning (ML)
and cloud computation, Structural Health Monitoring (SHM) based on a data-driven …

This comprehensive review paper examines the integration of Artificial Intelligence (AI) and
Machine Learning (ML) tools in earthquake engineering, specifically focusing on damage …

It has been proven that precise point positioning (PPP) is a well-established technique to
obtain high-precision positioning in the order between centimeters and millimeters. In this …

Feature Selection (FS) is an important step in data-driven structural health monitoring
approaches. In this paper, an Advanced version of the Binary Slime Mould Algorithm …

Bolts are typically deployed to unify disparate components in civil engineering structures,
making the surveillance of their tightness critical to ensuring the stability of such structures …

Bayesian finite element model updating has become an important tool for structural health
monitoring. However, it takes a large amount of computational cost to update the finite …

This paper presents a multi-objective AutoML algorithm to optimize the architecture and
hyperparameters of deep SHM models while maximizing the accuracy of networks and …

In fields where predictions may have vital consequences, uncertainty quantification (UQ)
plays a crucial role, as it enables more accurate forecasts and mitigates the potential risks …

This study addresses the challenge of multi-objective optimization of a composite shell
structure while adhering to constraints on the number of calls to a pseudo-experimental …

Prestressed high-strength (PHS) hollow square piles have been used recently to improve
the ability of structural foundations to resist uplift loads, and the connection between PHS …