Quantifying the value of positive transfer: An experimental case study
<|reference_start|>Quantifying the value of positive transfer: An experimental case study: In traditional approaches to structural health monitoring, challenges often arise associated with the availability of labelled data. Population-based structural health monitoring seeks to overcomes these challenges by leveraging data/information from similar structures via technologies such as transfer learning. The current paper demonstrate a methodology for quantifying the value of information transfer in the context of operation and maintenance decision-making. This demonstration, based on a population of laboratory-scale aircraft models, highlights the steps required to evaluate the expected value of information transfer including similarity assessment and prediction of transfer efficacy. Once evaluated for a given population, the value of information transfer can be used to optimise transfer-learning strategies for newly-acquired target domains.<|reference_end|>
@article{hughes2024quantifying,
    title={Quantifying the value of positive transfer: An experimental case study},
    author={Aidan J. Hughes, Giulia Delo, Jack Poole, Nikolaos Dervilis, Keith
  Worden},
    journal={arXiv preprint arXiv:2407.14342},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.14342},
    primaryClass={cs.LG}
}