A probabilistic metric for the validation of computational models
- Submitting institution
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The University of Liverpool
- Unit of assessment
- 12 - Engineering
- Output identifier
- 12629
- Type
- D - Journal article
- DOI
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10.1098/rsos.180687
- Title of journal
- Royal Society Open Science
- Article number
- 180687
- First page
- -
- Volume
- 5
- Issue
- 11
- ISSN
- 2054-5703
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2018
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
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3
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- A collaboration with the National Nuclear Laboratory [NNL] led to a new validation metric that provides the probability that predicted data fields belong to the same population as measured data fields [Dr Steve Graham, NNL, steve.graham@uknnl.com]. It was successfully demonstrated on three engineering exemplars and has led to new research with the US Air Force [grant #FA9550-17-1-0272], and an EU H2020 project [MOTIVATE grant #754660].
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -