Inference in hybrid Bayesian networks

Helge Langseth, Thomas D. Nielsen, Rumí, Rafael and Salmerón, Antonio

Reliability Engineering and System Safety, 2009, vol. 94, issue 10, 1499-1509

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.

Keywords: Bayesian networks; Reliability; Hybrid models; Inference (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:94:y:2009:i:10:p:1499-1509

DOI: 10.1016/j.ress.2009.02.027

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