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A Hybrid (Stochastic and Fuzzy) Methodology for Safety and Risk Assessment

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Probabilistic Safety Assessment and Management ’96

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Abstract

Probabilistic safety assessments (PSAs) and decision-support risk analyses frequently depend on data that are stochastically variable or subjectively uncertain. Probabilistic calculus approaches have been available to process stochastic variability data. There are now approaches using fuzzy mathematics for processing subjective uncertainty data. The incompatibilities in combining these approaches make hybrid analysis challenging. We have now developed a technique for performing hybrid (stochastic along with subjective) safety and risk analysis.

This work was supported by the United States Department of Energy under Contract DE-AC04-94AL85000.

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References

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Author information

Authors and Affiliations

  1. Sandia National Laboratories, Albuquerque, NM, USA, 87185-0490

    J. A. Cooper

Authors
  1. J. A. Cooper
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Editor information

Editors and Affiliations

  1. I A PSAM, Joint Research Centre, The European Commission, Institute for Systems, Informatics and Safety, 1-21020, ISPRA (Va), Italy

    P. Carlo Cacciabue PhD

  2. I A PSAM, NCSR ‘Demokritos’, PO Box 60228, GR-15310, Aghin Paraskevi, Greece

    Ioannis A. Papazoglou PhD

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© 1996 Springer-Verlag London

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Cooper, J.A. (1996). A Hybrid (Stochastic and Fuzzy) Methodology for Safety and Risk Assessment. In: Cacciabue, P.C., Papazoglou, I.A. (eds) Probabilistic Safety Assessment and Management ’96. Springer, London. https://doi.org/10.1007/978-1-4471-3409-1_68

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  • DOI: https://doi.org/10.1007/978-1-4471-3409-1_68

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-3411-4

  • Online ISBN: 978-1-4471-3409-1

  • eBook Packages: Springer Book Archive

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