DocumentCode
2084104
Title
Qualitative-Quantitative Bayesian Belief Networks for reliability and risk assessment
Author
Wang, Chengdong ; Mosleh, Ali
Author_Institution
Univ. of Maryland, College Park, MD, USA
fYear
2010
fDate
25-28 Jan. 2010
Firstpage
1
Lastpage
5
Abstract
This paper presents an extension of Bayesian belief networks (BBN) enabling use of both qualitative and quantitative likelihood scales in inference. The proposed method is accordingly named QQBBN (Qualitative-Quantitative Bayesian Belief Networks). The inclusion of qualitative scales is especially useful when quantitative data for estimation of probabilities are lacking and experts are reluctant to express their opinions quantitatively. In reliability and risk analysis such situation occurs when for example human and organizational root causes of systems are modeled explicitly. Such causes are often not quantifiable due to limitations in the state of the art and lack of proper quantitative metrics. This paper describes the proposed QQBBN framework and demonstrates its uses through a simple example.
Keywords
belief networks; estimation theory; fault trees; probability; reliability theory; risk analysis; QQBBN; probability estimation; qualitative-quantitative Bayesian belief network; reliability assessment; risk analysis; risk assessment; Application software; Artificial intelligence; Bayesian methods; Clustering algorithms; Humans; Inference algorithms; Power system modeling; Risk analysis; Risk management; Sociotechnical systems; Bayesian Belief Networks; Qualitative; Quantitative; Reliability; Risk;
fLanguage
English
Publisher
ieee
Conference_Titel
Reliability and Maintainability Symposium (RAMS), 2010 Proceedings - Annual
Conference_Location
San Jose, CA
ISSN
0149-144X
Print_ISBN
978-1-4244-5102-9
Electronic_ISBN
0149-144X
Type
conf
DOI
10.1109/RAMS.2010.5448022
Filename
5448022
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