1 citations · 1 across the 14 of their papers we have counts for
14 papers
On the use of Statistical Learning Theory for model selection in Structural Health Monitoring
C. A. Lindley, N. Dervilis, K. Worden
Whenever data-based systems are employed in engineering applications, defining an optimal statistical representation is subject to the problem of model selection. This paper focuss…
Regularising NARX models with multi-task learning
Sarah Bee, Lawrence Bull, Nikolaos Dervilis +1
A Nonlinear Auto-Regressive with eXogenous inputs (NARX) model can be used to describe time-varying processes; where the output depends on both previous outputs and current/previou…
When does a bridge become an aeroplane?
Tina A. Dardeno, Lawrence A. Bull, Nikolaos Dervilis +1
Despite recent advances in population-based structural health monitoring (PBSHM), knowledge transfer between highly-disparate structures (i.e., heterogeneous populations) remains a…
Quantifying the value of positive transfer: An experimental case study
Aidan J. Hughes, Giulia Delo, Jack Poole +2
In traditional approaches to structural health monitoring, challenges often arise associated with the availability of labelled data. Population-based structural health monitoring s…
Quantifying the value of information transfer in population-based SHM
Aidan J. Hughes, Jack Poole, Nikolaos Dervilis +2
Population-based structural health monitoring (PBSHM), seeks to address some of the limitations associated with data scarcity that arise in traditional SHM. A tenet of the populati…
Population-based wind farm monitoring based on a spatial autoregressive approach
W. Lin, K. Worden, E. J. Cross
An important challenge faced by wind farm operators is to reduce operation and maintenance cost. Structural health monitoring provides a means of cost reduction through minimising…