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Modelling the reliability of search and rescue operations with Bayesian Belief Networks

Norrington, L. and Quigley, J.L. and Russell, A.H. and Van Der Meer, R.B. (2008) Modelling the reliability of search and rescue operations with Bayesian Belief Networks. Reliability Engineering and System Safety, 93 (7). pp. 940-949. ISSN 0951-8320

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Abstract

This paper uses a Bayesian Belief Networks (BBN) methodology to model the reliability of Search And Rescue (SAR) operations within UK Coastguard (Maritime Rescue) coordination centres. This is an extension of earlier work, which investigated the rationale of the government's decision to close a number of coordination centres. The previous study made use of secondary data sources and employed a binary logistic regression methodology to support the analysis. This study focused on the collection of primary data through a structured elicitation process, which resulted in the construction of a BBN. The main findings of the study are that statistical analysis of secondary data can be used to complement BBNs. The former provided a more objective assessment of associations between variables, but was restricted in the level of detail that could be explicitly expressed within the model due to a lack of available data. The latter method provided a much more detailed model, but the validity of the numeric assessments was more questionable. Each method can be used to inform and defend the development of the other. The paper describes in detail the elicitation process employed to construct the BBN and reflects on the potential for bias.

Item type: Article
ID code: 7379
Keywords: Bayesian belief networks, statistical inference, elicitation, expert judgement, reliability modelling, risk assessment, Management. Industrial Management, Applied Mathematics, Industrial and Manufacturing Engineering, Safety, Risk, Reliability and Quality
Subjects: Social Sciences > Industries. Land use. Labor > Management. Industrial Management
Department: Strathclyde Business School > Management Science
Related URLs:
    Depositing user: Strathprints Administrator
    Date Deposited: 02 Feb 2009 11:04
    Last modified: 04 Sep 2014 18:29
    URI: http://strathprints.strath.ac.uk/id/eprint/7379

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