Bayesian probabilistic network approach for managing earthquake risks of cities

Yahya Bayraktarli, Michael Faber

    Research output: Contribution to journalJournal articleResearch


    This paper considers the application of Bayesian probabilistic networks (BPNs) to large-scale risk based decision making in regard to earthquake risks. A recently developed risk management framework is outlined which utilises Bayesian probabilistic modelling, generic indicator based risk models and geographical information systems. The proposed framework comprises several modules: A module on the probabilistic description of potential future earthquake shaking intensity, a module on the probabilistic assessment of spatial variability of soil liquefaction, a module on damage assessment of buildings and a fourth module on the consequences of an earthquake. Each of these modules is integrated into a BPN. Special attention is given to aggregated risk, i.e. the risk contribution from assets at multiple locations in a city subjected to the same earthquake. The application of the methodology is illustrated on an example considering a portfolio of reinforced concrete structures in a city located close to the
    western part of the North Anatolian Fault in Turkey.
    Original languageEnglish
    Issue number1
    Pages (from-to)2-24
    Publication statusPublished - 2011


    • Portfolio seismic risk
    • Loss exceedance curve
    • Common cause effects


    Dive into the research topics of 'Bayesian probabilistic network approach for managing earthquake risks of cities'. Together they form a unique fingerprint.

    Cite this