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A Bayesian kernel approach to modeling resilience-based network component importance

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  • Baroud, Hiba
  • Barker, Kash

Abstract

The resilience of infrastructure networks is an increasingly important consideration in infrastructure planning and risk management. One aspect of resilience-based planning is determining which components in the network are most important to the resilience of the network. This work makes use of a resilience-based component importance measure, the resilience worth, and proposes to model this measure under uncertainty using a Bayesian kernel technique. Such a technique can be useful in modeling component importance as it enables the probability distribution for the importance measure to be updated using data and prior information with a Bayesian kernel model. The proposed approach is applied to study the importance of locks and dams along the Mississippi River Navigation System. The highest predictive overall accuracy is achieved with a uniform prior distribution, and using the posterior distribution and a multicriteria decision analysis technique, we identify the five locks and dams with the largest impact on the system's resilience.

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  • Baroud, Hiba & Barker, Kash, 2018. "A Bayesian kernel approach to modeling resilience-based network component importance," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 10-19.
    • Handle: RePEc:eee:reensy:v:170:y:2018:i:c:p:10-19
    DOI: 10.1016/j.ress.2017.09.022
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    References listed on IDEAS

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    1. Ramirez-Marquez, Jose E. & Rocco, Claudio M. & Gebre, Bethel A. & Coit, David W. & Tortorella, Michael, 2006. "New insights on multi-state component criticality and importance," Reliability Engineering and System Safety, Elsevier, vol. 91(8), pages 894-904.
    2. Baroud, Hiba & Barker, Kash & Ramirez-Marquez, Jose E. & Rocco S., Claudio M., 2014. "Importance measures for inland waterway network resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 55-67.
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    4. Hosseini, Seyedmohsen & Barker, Kash & Ramirez-Marquez, Jose E., 2016. "A review of definitions and measures of system resilience," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 47-61.
    5. Henry, Devanandham & Emmanuel Ramirez-Marquez, Jose, 2012. "Generic metrics and quantitative approaches for system resilience as a function of time," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 114-122.
    6. Rocco S., Claudio M. & Ramirez-Marquez, Jose Emmanuel, 2012. "Innovative approaches for addressing old challenges in component importance measures," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 123-130.
    7. Barker, Kash & Ramirez-Marquez, Jose Emmanuel & Rocco, Claudio M., 2013. "Resilience-based network component importance measures," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 89-97.
    8. Zio, Enrico & Marella, Marco & Podofillini, Luca, 2007. "Importance measures-based prioritization for improving the performance of multi-state systems: application to the railway industry," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1303-1314.
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