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Found 8 papers, 0 papers with code
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 SHM.
Sharing Information Between Machine Tools to Improve Surface Finish Forecasting
At present, most surface-quality prediction methods can only perform single-task prediction which results in under-utilised datasets, repetitive work and increased experimental costs.
A decision framework for selecting information-transfer strategies in population-based SHM
Decision-support for the operation and maintenance of structures provides significant motivation for the development and implementation of structural health monitoring (SHM) systems.
Towards risk-informed PBSHM: Populations as hierarchical systems
The current paper presents a formal representation of populations of structures, such that risk-based decision processes may be specified within them.
Mitigating sampling bias in risk-based active learning via an EM algorithm
For SHM applications, the value of information is evaluated with respect to a maintenance decision process, and the data-label querying corresponds to the inspection of a structure to determine its health state.
Improving decision-making via risk-based active learning: Probabilistic discriminative classifiers
For risk-based active learning in SHM, the value of information is evaluated with respect to a maintenance decision process, and the data-label querying corresponds to the inspection of a structure to determine its health state.
On robust risk-based active-learning algorithms for enhanced decision support
In contrast, the discriminative classifiers are shown to have excellent robustness to the effects of sampling bias.
A probabilistic risk-based decision framework for structural health monitoring
Obtaining the ability to make informed decisions regarding the operation and maintenance of structures, provides a major incentive for the implementation of structural health monitoring (SHM) systems.
Decision Making
Decision Making Under Uncertainty
Applications
