DocumentCode
3436152
Title
Component importance and sensitivity analysis in Bayesian networks
Author
Xiaopin Zhong ; Qiu Li
Author_Institution
Coll. of Mechatron. & Control Eng., Shenzhen Univ., Shenzhen, China
fYear
2013
fDate
15-18 July 2013
Firstpage
320
Lastpage
325
Abstract
In this paper, component importance and sensitivity analysis in Bayesian networks are reviewed and a strategy for the case of non-deterministic structures is proposed. A complex system example is analyzed by the methods of Birnbaum´s derivative, variance-based sensitivity analysis in deterministic structures and non-deterministic structures respectively. The results are compared and demonstrate the feasibility of the proposed strategy for non-deterministic structures in Bayesian networks.
Keywords
belief networks; Bayesian networks; Birnbaum derivative; component importance; deterministic structures; nondeterministic structures; variance-based sensitivity analysis; Mathematical model; Pollution measurement; Reactive power; Reliability; Sensitivity analysis; Uncertainty; Bayesian networks; component importance; non-deterministic structure; sensitivity analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE), 2013 International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4799-1014-4
Type
conf
DOI
10.1109/QR2MSE.2013.6625593
Filename
6625593
Link To Document