IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v94y2009i10p1499-1509.html
   My bibliography  Save this article

Inference in hybrid Bayesian networks

Author

Listed:
  • Langseth, Helge
  • Nielsen, Thomas D.
  • Rumí, Rafael
  • Salmerón, Antonio

Abstract

Since the 1980s, Bayesian networks (BNs) have become increasingly popular for building statistical models of complex systems. This is particularly true for boolean systems, where BNs often prove to be a more efficient modelling framework than traditional reliability techniques (like fault trees and reliability block diagrams). However, limitations in the BNs’ calculation engine have prevented BNs from becoming equally popular for domains containing mixtures of both discrete and continuous variables (the so-called hybrid domains). In this paper we focus on these difficulties, and summarize some of the last decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:94:y:2009:i:10:p:1499-1509
    DOI: 10.1016/j.ress.2009.02.027
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832009000581
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2009.02.027?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. Langseth, Helge & Portinale, Luigi, 2007. "Bayesian networks in reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 92-108.
    2. Rafael Rumí & Antonio Salmerón & Serafín Moral, 2006. "Estimating mixtures of truncated exponentials in hybrid bayesian networks," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 15(2), pages 397-421, September.
    3. Christofides, A. & Tanyi, B. & Christofides, S. & Whobrey, D. & Christofides, N., 1999. "The optimal discretization of probability density functions," Computational Statistics & Data Analysis, Elsevier, vol. 31(4), pages 475-486, October.
    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. 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).
    2. Häger, David & Andersen, Lasse B., 2010. "A knowledge based approach to loss severity assessment in financial institutions using Bayesian networks and loss determinants," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1635-1644, December.
    3. Bhardwaj, U. & Teixeira, A.P. & Guedes Soares, C., 2022. "Bayesian framework for reliability prediction of subsea processing systems accounting for influencing factors uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    4. Taleb-Berrouane, Mohammed & Khan, Faisal & Amyotte, Paul, 2020. "Bayesian Stochastic Petri Nets (BSPN) - A new modelling tool for dynamic safety and reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    5. 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).
    6. 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).
    7. 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.
    8. 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.
    9. 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.
    10. Wu, Bing & Tang, Yuheng & Yan, Xinping & Guedes Soares, Carlos, 2021. "Bayesian Network modelling for safety management of electric vehicles transported in RoPax ships," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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).
    17. Wallstrom, Timothy C., 2011. "Quantification of margins and uncertainties: A probabilistic framework," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 1053-1062.

    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. Pan, Yue & Ou, Shenwei & Zhang, Limao & Zhang, Wenjing & Wu, Xianguo & Li, Heng, 2019. "Modeling risks in dependent systems: A Copula-Bayesian approach," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 416-431.
    2. Rogerson, Ellen C. & Lambert, James H., 2012. "Prioritizing risks via several expert perspectives with application to runway safety," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 22-34.
    3. Ibsen Chivatá Cárdenas & Saad S.H. Al‐Jibouri & Johannes I.M. Halman & Frits A. van Tol, 2014. "Modeling Risk‐Related Knowledge in Tunneling Projects," Risk Analysis, John Wiley & Sons, vol. 34(2), pages 323-339, February.
    4. 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.
    5. George-Williams, Hindolo & Patelli, Edoardo, 2017. "Efficient availability assessment of reconfigurable multi-state systems with interdependencies," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 431-444.
    6. Vimal Vijayan & Sanjay K Chaturvedi, 2021. "Multi-component maintenance grouping optimization based on stochastic dependency," Journal of Risk and Reliability, , vol. 235(2), pages 293-305, April.
    7. Vimal Vijayan & Sanjay K Chaturvedi & Ritesh Chandra, 2020. "A failure interaction model for multicomponent repairable systems," Journal of Risk and Reliability, , vol. 234(3), pages 470-486, June.
    8. Michail Cheliotis & Evangelos Boulougouris & Nikoletta L Trivyza & Gerasimos Theotokatos & George Livanos & George Mantalos & Athanasios Stubos & Emmanuel Stamatakis & Alexandros Venetsanos, 2021. "Review on the Safe Use of Ammonia Fuel Cells in the Maritime Industry," Energies, MDPI, vol. 14(11), pages 1-20, May.
    9. Babaleye, Ahmed O. & Kurt, Rafet Emek & Khan, Faisal, 2019. "Safety analysis of plugging and abandonment of oil and gas wells in uncertain conditions with limited data," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 133-141.
    10. Ait Mokhtar, El Hassene & Laggoune, Radouane & Chateauneuf, Alaa, 2023. "Imperfect maintenance modeling and assessment of repairable multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    11. Iamsumang, Chonlagarn & Mosleh, Ali & Modarres, Mohammad, 2018. "Monitoring and learning algorithms for dynamic hybrid Bayesian network in on-line system health management applications," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 118-129.
    12. Daniele Codetta-Raiteri & Luigi Portinale, 2014. "Approaching dynamic reliability with predictive and diagnostic purposes by exploiting dynamic Bayesian networks," Journal of Risk and Reliability, , vol. 228(5), pages 488-503, October.
    13. Penttinen, Jussi-Pekka & Niemi, Arto & Gutleber, Johannes & Koskinen, Kari T. & Coatanéa, Eric & Laitinen, Jouko, 2019. "An open modelling approach for availability and reliability of systems," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 387-399.
    14. Maria Elena De Giuli & Alessandro Greppi & Marina Resta, 2019. "An Object-Oriented Bayesian Framework for the Detection of Market Drivers," Risks, MDPI, vol. 7(1), pages 1-18, January.
    15. Xiahou, Tangfan & Zheng, Yi-Xuan & Liu, Yu & Chen, Hong, 2023. "Reliability modeling of modular k-out-of-n systems with functional dependency: A case study of radar transmitter systems," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    16. Seyedmohsen Hosseini & Dmitry Ivanov, 2022. "A new resilience measure for supply networks with the ripple effect considerations: a Bayesian network approach," Annals of Operations Research, Springer, vol. 319(1), pages 581-607, December.
    17. Zhong, Shengtong & Langseth, Helge & Nielsen, Thomas Dyhre, 2014. "A classification-based approach to monitoring the safety of dynamic systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 61-71.
    18. Bandeira, Michelle Carvalho Galvão Silva Pinto & Correia, Anderson Ribeiro & Martins, Marcelo Ramos, 2018. "General model analysis of aeronautical accidents involving human and organizational factors," Journal of Air Transport Management, Elsevier, vol. 69(C), pages 137-146.
    19. El-Awady, Ahmed & Ponnambalam, Kumaraswamy, 2021. "Integration of simulation and Markov Chains to support Bayesian Networks for probabilistic failure analysis of complex systems," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    20. 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.

    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:94:y:2009:i:10:p:1499-1509. 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.