Multiattribute multitask transformer framework for vision‐based structural health monitoring
Using deep learning (DL) to recognize building and infrastructure damage via images is
becoming popular in vision‐based structural health monitoring (SHM). However, many …
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
Centralized traffic signal control has long been a challenging, high‐dimensional
optimization problem. This study establishes a simulation‐based optimization framework …
optimization problem. This study establishes a simulation‐based optimization framework …
[HTML][HTML] On the hierarchical Bayesian modelling of frequency response functions
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 …
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
Structural health monitoring (SHM) involves continuously surveilling the performance of
structures to identify progressive damage or deterioration that might evolve over time …
structures to identify progressive damage or deterioration that might evolve over time …
Quantifying the value of information transfer in population-based SHM
Population-based structural health monitoring (PBSHM) seeks to address some of the
limitations associated with data scarcity that arise in traditional structural health monitoring …
limitations associated with data scarcity that arise in traditional structural health monitoring …
Characterization of mechanical properties of shale constituent minerals using phase‐identified nanoindentation
Abstract Characterization of mechanical properties of shale constituent minerals (viz., the
mechanical genes of shale) has been challenging but of great significance for engineering …
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
The presence of sufficient labelled data associated to various environmental conditions and
damage scenarios often represents a challenge for the applicability of supervised-learning …
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 …
structural operation and management grows. This can be achieved by using structural …
Encoding domain expertise into multilevel models for source location
Data from populations of systems are prevalent in many industrial applications. Machines
and infrastructure are increasingly instrumented with sensing systems, emitting streams of …
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 …
learning state can be realized through the comprehensive analysis of students face …