IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v153y2016icp96-109.html
   My bibliography  Save this article

A discretization procedure for rare events in Bayesian networks

Author

Listed:
  • Zwirglmaier, Kilian
  • Straub, Daniel

Abstract

Discrete Bayesian networks (BNs) can be effective for risk- and reliability assessments, in which probability estimates of (rare) failure events are frequently updated with new information. To solve such reliability problems accurately in BNs, the discretization of continuous random variables must be performed carefully. To this end, we develop an efficient discretization scheme, which is based on finding an optimal discretization for the linear approximation of the reliability problem obtained from the First-Order Reliability Method (FORM). Because the probability estimate should be accurate under all possible future information scenarios, the discretization scheme is optimized with respected to the expected posterior error. To simplify application of the method, we establish parametric formulations for efficient discretization of random variables in BNs for reliability problems based on numerical investigations. The procedure is implemented into a software prototype. Finally, it is applied to a verification example and an application example, the prediction of runway overrun of a landing aircraft.

Suggested Citation

  • Zwirglmaier, Kilian & Straub, Daniel, 2016. "A discretization procedure for rare events in Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 96-109.
  • Handle: RePEc:eee:reensy:v:153:y:2016:i:c:p:96-109
    DOI: 10.1016/j.ress.2016.04.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832016300229
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2016.04.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhu, Jiandao & Collette, Matthew, 2015. "A dynamic discretization method for reliability inference in Dynamic Bayesian Networks," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 242-252.
    2. Langseth, Helge & Nielsen, Thomas D. & Rumí, Rafael & Salmerón, Antonio, 2009. "Inference in hybrid Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1499-1509.
    3. Neil, Martin & Tailor, Manesh & Marquez, David & Fenton, Norman & Hearty, Peter, 2008. "Modelling dependable systems using hybrid Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 933-939.
    4. Hanea, Anca & Morales Napoles, Oswaldo & Ababei, Dan, 2015. "Non-parametric Bayesian networks: Improving theory and reviewing applications," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 265-284.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Simon, Christophe & Bicking, Frédérique, 2017. "Hybrid computation of uncertainty in reliability analysis with p-box and evidential networks," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 629-638.
    2. Tosoni, E. & Salo, A. & Govaerts, J. & Zio, E., 2019. "Comprehensiveness of scenarios in the safety assessment of nuclear waste repositories," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 561-573.
    3. Byun, Ji-Eun & Song, Junho, 2021. "A general framework of Bayesian network for system reliability analysis using junction tree," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    4. Lee, Dooyoul & Kwon, Kybeom, 2023. "Dynamic Bayesian network model for comprehensive risk analysis of fatigue-critical structural details," Reliability Engineering and System Safety, Elsevier, vol. 229(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yan-Feng Li & Jinhua Mi & Yu Liu & Yuan-Jian Yang & Hong-Zhong Huang, 2015. "Dynamic fault tree analysis based on continuous-time Bayesian networks under fuzzy numbers," Journal of Risk and Reliability, , vol. 229(6), pages 530-541, December.
    2. Marquez, David & Neil, Martin & Fenton, Norman, 2010. "Improved reliability modeling using Bayesian networks and dynamic discretization," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 412-425.
    3. Wang, Fan & Li, Heng & Dong, Chao & Ding, Lieyun, 2019. "Knowledge representation using non-parametric Bayesian networks for tunneling risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    4. Zhong, X. & Ichchou, M. & Saidi, A., 2010. "Reliability assessment of complex mechatronic systems using a modified nonparametric belief propagation algorithm," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1174-1185.
    5. Daniel Puig & Oswaldo Morales-Nápoles & Fatemeh Bakhtiari & Gissela Landa, 2017. "The accountability imperative for quantifiying the uncertainty of emission forecasts : evidence from Mexico," Working Papers hal-03389325, HAL.
    6. Daniel Puig & Oswaldo Morales-Nápoles & Fatemeh Bakhtiari & Gissela Landa, 2017. "The accountability imperative for quantifiying the uncertainty of emission forecasts : evidence from Mexico," SciencePo Working papers Main hal-03389325, HAL.
    7. Chih-Hao Wen & Ping-Yu Hsu & Ming-Shien Cheng, 2017. "Applying intelligent methods in detecting maritime smuggling," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(3), pages 573-599, August.
    8. Costa, Rodrigo & Haukaas, Terje & Chang, Stephanie E. & Dowlatabadi, Hadi, 2019. "Object-oriented model of the seismic vulnerability of the fuel distribution network in coastal British Columbia," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 11-23.
    9. Nogal, Maria & Morales Nápoles, Oswaldo & O’Connor, Alan, 2019. "Structured expert judgement to understand the intrinsic vulnerability of traffic networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 136-152.
    10. Bensi, Michelle & Kiureghian, Armen Der & Straub, Daniel, 2013. "Efficient Bayesian network modeling of systems," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 200-213.
    11. Wallstrom, Timothy C., 2011. "Quantification of margins and uncertainties: A probabilistic framework," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 1053-1062.
    12. Morales-Nápoles, Oswaldo & Steenbergen, Raphaël D.J.M., 2014. "Analysis of axle and vehicle load properties through Bayesian Networks based on Weigh-in-Motion data," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 153-164.
    13. Zhu, Jiandao & Collette, Matthew, 2015. "A dynamic discretization method for reliability inference in Dynamic Bayesian Networks," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 242-252.
    14. Lan, Meng & Zhu, Jiping & Lo, Siuming, 2021. "Hybrid Bayesian network-based landslide risk assessment method for modeling risk for industrial facilities subjected to landslides," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    15. Bhardwaj, U. & Teixeira, A.P. & Guedes Soares, C. & Ariffin, A.K. & Singh, S.S., 2021. "Evidence based risk analysis of fire and explosion accident scenarios in FPSOs," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    16. Bismut, Elizabeth & Straub, Daniel, 2021. "Optimal adaptive inspection and maintenance planning for deteriorating structural systems," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    17. Adedipe, Tosin & Shafiee, Mahmood & Zio, Enrico, 2020. "Bayesian Network Modelling for the Wind Energy Industry: An Overview," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    18. Rajabzadeh, Vida & Hekmatzadeh, Ali Akbar & Tabatabaie Shourijeh, Piltan & Torabi Haghighi, Ali, 2023. "Introducing a probabilistic framework to measure dam overtopping risk for dams benefiting from dual spillways," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    19. Zhao, Tengyuan & Wang, Yu, 2020. "Non-parametric simulation of non-stationary non-gaussian 3D random field samples directly from sparse measurements using signal decomposition and Markov Chain Monte Carlo (MCMC) simulation," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    20. Mendoza-Lugo, Miguel Angel & Morales-Nápoles, Oswaldo, 2024. "Mapping hazardous locations on a road network due to extreme gross vehicle weights," Reliability Engineering and System Safety, Elsevier, vol. 242(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:153:y:2016:i:c:p:96-109. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.