A Three-Part Bayesian Network for Modeling Dwelling Fires and Their Impact upon People and Property
- Submitting institution
-
Liverpool John Moores University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 1197
- Type
- D - Journal article
- DOI
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10.1111/risa.13113
- Title of journal
- Risk Analysis
- Article number
- -
- First page
- 2087
- Volume
- 38
- Issue
- 10
- ISSN
- 0272-4332
- Open access status
- Access exception
- Month of publication
- March
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
B - LOOM
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work resulted from a collaboration with Merseyside Fire and Rescue Service (MFRS), supported by EPSRC (EP/F041993/1) and Leverhulme Trust (Research Fellowship-RF/7/RFG/2010/0019). It has influenced and underpinned MFRS’s combined risk management approach since 2017. It has improved fire-fighting personnel training efficiencies (200 members and 22 stations) through resource rationalisation (Station Manager, markpthomas@merseyfire.gov.uk). The work has been used by MFRS and beyond (www.local.gov.uk/sites/default/files/documents/merseyside-fire-and-rescu-bdc.pdf), and contributed to maintaining MFRS as the highest performing fire service in the UK (https://www.justiceinspectorates.gov.uk/hmicfrs/publications/frs-assessment-2018-19-merseyside/). It resulted in an EU-MSCA Individual Fellowship award (€225k/2020-2022/STOPFIRE). The work has led to two fully-funded keynote addresses (ICIME 2019-http://www.icime.org/; SMRLO2019- http://smrlo2019.bit.edu.cn/).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -