Multiattribute multitask transformer framework for vision‐based structural health monitoring

Y Gao, J Yang, H Qian… - Computer‐Aided Civil and …, 2023 - Wiley Online Library
Using deep learning (DL) to recognize building and infrastructure damage via images is
becoming popular in vision‐based structural health monitoring (SHM). However, many …

Optimizing green splits in high‐dimensional traffic signal control with trust region Bayesian optimization

Y Gong, S Zhong, S Zhao, F Xiao… - Computer‐Aided Civil …, 2024 - Wiley Online Library
Centralized traffic signal control has long been a challenging, high‐dimensional
optimization problem. This study establishes a simulation‐based optimization framework …

[HTML][HTML] On the hierarchical Bayesian modelling of frequency response functions

TA Dardeno, K Worden, N Dervilis, RS Mills… - Mechanical Systems and …, 2024 - Elsevier
Structural health monitoring (SHM) strategies seek to evaluate, predict, and maintain
structural integrity, to improve the safety and design service life of structures in operation …

[HTML][HTML] Combining transfer learning and numerical modelling to deal with the lack of training data in data-based SHM

RS Battu, K Agathos, JML Monsalve, K Worden… - Journal of Sound and …, 2025 - Elsevier
Structural health monitoring (SHM) involves continuously surveilling the performance of
structures to identify progressive damage or deterioration that might evolve over time …

Quantifying the value of information transfer in population-based SHM

AJ Hughes, J Poole, N Dervilis, P Gardner… - IMAC, A Conference and …, 2024 - Springer
Population-based structural health monitoring (PBSHM) seeks to address some of the
limitations associated with data scarcity that arise in traditional structural health monitoring …

Characterization of mechanical properties of shale constituent minerals using phase‐identified nanoindentation

J Du, KV Yuen, AJ Whittle, L Hu… - … ‐Aided Civil and …, 2024 - Wiley Online Library
Abstract Characterization of mechanical properties of shale constituent minerals (viz., the
mechanical genes of shale) has been challenging but of great significance for engineering …

[HTML][HTML] Transfer learning in bridge monitoring: Laboratory study on domain adaptation for population-based SHM of multispan continuous girder bridges

V Giglioni, J Poole, R Mills, I Venanzi, F Ubertini… - … Systems and Signal …, 2025 - Elsevier
The presence of sufficient labelled data associated to various environmental conditions and
damage scenarios often represents a challenge for the applicability of supervised-learning …

On decision-theoretic model assessment for structural deterioration monitoring

NE Silionis, KN Anyfantis - Mechanical Systems and Signal Processing, 2025 - Elsevier
As data from monitored structures become more available, the demand for its efficient use in
structural operation and management grows. This can be achieved by using structural …

Encoding domain expertise into multilevel models for source location

LA Bull, MR Jones, EJ Cross, A Duncan… - arXiv preprint arXiv …, 2023 - arxiv.org
Data from populations of systems are prevalent in many industrial applications. Machines
and infrastructure are increasingly instrumented with sensing systems, emitting streams of …

[PDF][PDF] Image recognition algorithm based on improved AlexNet and shared parameter transfer learning

JL Lu, XT Wan - Academic Journal of Computing & Information …, 2022 - francis-press.com
With the development of artificial intelligence technology, the basic judgment of students
learning state can be realized through the comprehensive analysis of students face …