Solving dynamic fault trees using a new hybrid Bayesian network inference algorithm

2008 Mediterranean Conference on Control and Automation - Conference Proceedings, MED'08

Volumn , Issue , 2008, Pages 609-614

  Marquez, David ^a   Neil, Martin ^a,b   Fenton, Norman ^a,b  

^a QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

^b Cambridge   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATE INFERENCE; BAYESIAN; BAYESIAN NETWORK INFERENCE; COMMON CAUSE FAILURE; CONDITIONAL PROBABILITY TABLES; CONTINUOUS VARIABLES; CONTROL AND AUTOMATION; DYNAMIC FAULT TREES; EXPERT JUDGEMENTS; FAILURE DATA; FAILURE DISTRIBUTIONS; NUMERICAL INTEGRATION TECHNIQUES; PRIOR INFORMATION; SIMULATION METHODS; STATIC AND DYNAMIC;

APPROXIMATION ALGORITHMS; BAYESIAN NETWORKS; DISTRIBUTED PARAMETER NETWORKS; FAILURE ANALYSIS; HYBRID SENSORS; INDUSTRIAL ENGINEERING; INFERENCE ENGINES; INTEGRATION; INTELLIGENT NETWORKS; LARGE SCALE SYSTEMS; NUMERICAL ANALYSIS; PROBABILITY DISTRIBUTIONS; QUALITY ASSURANCE; RELIABILITY; RISK ASSESSMENT; SAFETY FACTOR; SPEECH ANALYSIS; SYSTEMS ENGINEERING; TREES (MATHEMATICS); UNCERTAINTY ANALYSIS;

SENSITIVITY ANALYSIS;

EID: 52949136646     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MED.2008.4602222     Document Type: Conference Paper

References (31)

1. Agena Ltd. 2007. AgenaRisk software package, www.AgenaRisk.com.
2. Amari, S., Dill, G., Howald, E. (2003). A new approach to solve dynamic fault trees. Reliab Maintainability Symp, 374-379.
3. Bobbio A, Portinale L, Minichino M, and Ciancamerla E. (2001). Improving the analysis of dependable systems by mapping fault trees into Bayesian networks. Reliability Engineering and System Safety 71 (3), 249-260.
4. Boudali H, Dugan J. B. (2005). A discrete-time Bayesian network reliability modeling and analysis framework. Reliability Engineering and System Safety, vol. 87, no. 3, 337-349.
5. Dugan J.B., Bavuso S. J. and Boyd M.A. (1992). Dynamic Fault Tree models for Fault Tolerant Computer Systems, IEEE Trans. Reliability, vol. 41, 363-377.
6. Fenton NE, Krause P, Neil M. (2002). Probabilistic Modelling for Software Quality Control, Journal of Applied Non-Classical Logics 12(2), 173-188.
7. Fenton N, Littlewood B, Neil M, Strigini L, Sutcliffe A, Wright D. (1998). Assessing Dependability of Safety Critical Systems using Diverse Evidence, IEE Proceedings Software Engineering, 145(1), 35-39.
8. Fenton N and Neil M. (1999). 'A Critique of Software Defect Prediction Models, IEEE Transactions on Software Engineering, 25(5), 675-689.
9. Ghahramani, Z. (1997). Learning dynamic Bayesian networks. In C. Giles and M. Gori (Eds.), Adaptive Processing of Sequences and Data Structures, Lecture Notes in Artificial Intelligence, pp. 168-197. Berlin: Springer Verlag.
10. Gulati R. and Dugan J. B. (1997). A modular approach for analyzing static and dynamic fault trees, in Proc. Ann. Reliability and Maintainability Symp., 57-63.
11. Jensen F. (2001). Bayesian Networks and Decision Graph, Springer.
12. Jensen F, Lauritzen S.L, Olesen K. (1990). Bayesian updating in recursive graphical models by local computations, Computational Statistics Quarterly, 4, 260-282.
13. Kozlov A.V, Koller D. (1997). Nonuniform dynamic discretization in hybrid networks, in D. Geiger and P.P. Shenoy (eds.), Uncertainty in Artificial Intelligence, 13, pp. 314-325.
14. Kullback, S., and Leibler, R. A., 1951, On information and sufficiency, Annals of Mathematical Statistics 22: 79-86.
15. Langseth, H., and Portinale, L. (2006). Bayesian networks in reliability, Reliability Engineering and System Safety. (Also available as Technical Report No. TR-INF-2005-04-01-UNIPMN, Dept. of Computer Science, University of Eastern Piedmont "Amedeo Avogadro", Alessandria, Italy).
16. Lauritzen S.L. (1996). Graphical Models, Oxford.
17. Lauritzen S.L., and Speigelhalter D.J. (1998). Local Computations with Probabilities on Graphical Structures and their Application to Expert Systems (with discussion), Journal of the Royal Statistical Society Series B, Vol. 50, No 2, 157-224.
18. Marquez D, Neil M, and Fenton N. (2007). Improved reliability modelling using Bayesian networks and dynamic discretisation, (submitted to IEEE Trans. Reliability).
19. Montani S, Portinale L, Bobbio A. (2005). Dynamic Bayesian networks for modeling advanced fault tree features in dependability analysis, In: Proceedings of the sixteenth European conference on safety and reliability. Leiden, pp. 1415-22. The Netherlands: A.A. Balkema.
20. Murphy K. (2002). Dynamic Bayesian Networks: Representation, Inference and Learning, PhD thesis, Dept. Computer Science, UC Berkeley.
21. Neil M, Fenton N, Forey S, Harris R. (2002). Using Bayesian Belief Networks to Predict the Reliability of Military Vehicles, IEE Computing and Control Engineering, 12(1), 11-20.
22. Neil M., Krause P., and Fenton N. (2003). Software Quality Prediction Using Bayesian Networks in Software Engineering with Computational Intelligence, edited by Khoshgoftaar T. M. The Kluwer International Series in Engineering and Computer Science, Volume 73.
23. Neil M, Tailor M, Marquez D. Inference in Bayesian Networks using Dynamic Discretisation, Statistics and Computing Journal, Springer Netherlands, Vol. 17, Number 3, September 2007.
24. Neil M, Tailor M, Marquez D, Fenton N. and Hearty P. (2007) Modelling Dependable Systems using Hybrid Bayesian Networks, Reliability Engineering and System Safety, (to appear).
25. Pearl, J. (1993). Graphical models, causality, and intervention, Statistical Science, Vol. 8, no. 3, 266-273.
26. Portinale L, Bobbio A. (1999). Bayesian networks for dependability analysis: an application to digital control reliability, In: Proceedings of the fifteenth conference on uncertainty in artificial intelligence. San Francisco, CA: Morgan Kaufmann Publishers.
27. Schneeweiss W. G. (1999). The Fault Tree Method. LiLoLe Verlag.
28. Solano-Soto J, Sucar, LE. (2001). A methodology for reliable system design, In: Proceedings of the 4th international conference on industrial and engineering applications of artificial intelligence and expert systems, Lecture notes in artificial intelligence, vol. 2070, pp. 734-45. Berlin, Germany: Springer.
29. Torres-Toledano JG, Sucar LE. (1998). Bayesian networks for reliability analysis of complex systems, In: Proceedings of the 6th Ibero-American conference on AI (IBERAMIA 98), Lecture notes in artificial intelligence, vol. 1484, pp. 195-206. Berlin, Germany: Springer.
30. Watson H. A. and Bell Telephone Laboratories. (1961). Launch Control Safety Study, Bell Telephone Laboratories, Murray Hill, NJ USA.
31. Weber P, Jouffe L. (2003). Reliability modeling with Dynamic Bayesian Networks, 5th IFAC Sysmposium on Fault Detection, Supervision and Safety of Technical Processes, Washington, D.C., USA.J.B. Dugan, S. J. Bavuso and M.A. Boyd, "Dynamic Fault Tree models for Fault Tolerant Computer Systems", IEEE Trans. Reliability, vol 41, 1992, pp. 363-377.