Dynamic system safety analysis in HiP-HOPS with Petri Nets and Bayesian Networks
- Submitting institution
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The University of Bradford
- Unit of assessment
- 12 - Engineering
- Output identifier
- 103
- Type
- D - Journal article
- DOI
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10.1016/j.ssci.2018.02.001
- Title of journal
- Safety Science
- Article number
- -
- First page
- 55
- Volume
- 105
- Issue
- -
- ISSN
- 0925-7535
- Open access status
- Technical exception
- Month of publication
- -
- Year of publication
- 2018
- URL
-
https://www.sciencedirect.com/science/article/pii/S0925753517314911?via%3Dihub
- 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
-
2
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Undertaken within Horizon 2020 DEIS project (grant: 732242), this work develops methodologies to apply Bayesian Networks and Petri Nets for model-based analysis of time-dependent dynamic behaviour of complex systems with limited observability of data. This work is significant because it enhanced the capability of HiP-HOPS (http://hip-hops.eu/), a state-of-the-art tool recognised by the research community in the area of dependability analysis and used by several industries. This new development of HiP-HOPS has been put forward as one of the candidate technologies to be used in a new EU project called “Secure and Safe Multi-Robot Systems”.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
