Abstract Structural Health Monitoring (SHM) enables the rapid assessment of structural
integrity in the immediate aftermath of strong ground motions. Data-driven techniques, often …

In recent years, increasingly complex machine learning methods have become state-of-the-
art in modelling wind turbine power curves based on operational data. While these methods …

(AI) and Machine Learning (ML) are set to revolutionize all industries, Intelligent
Transportation Systems (ITS) field is no exception. However, being a safety-critical system …

The problem of estimating earthquake risk is one of the primary themes for researchers and
investigators in the field of geosciences. The combined assessment of spatial probability …

The posterior statistical distributions of fatigue strength are determined using Bayesian
inferential statistics and the Metropolis Monte Carlo method. This study explores how …

This research addresses a critical challenge in aerospace engineering: enhancing the
interpretability of machine learning models for predictive maintenance. By integrating …

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of
maintenance management, shielding public safety and economic sustainability. Although …

Lattice structures created using additive manufacturing technology inevitably produce
inherent defects that seriously affect their mechanical properties. Predicting and analysing …

Estimating analytical fragility functions requires high computational costs due to numerous
incremental non-linear dynamic analyses. This study employs a soft computing approach to …

Studies on understanding the regional seismological differences based on the variations in
the characteristics of the ground motion waves recorded during seismic events have …