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4.8.4 Four Applications of Bayesian Networks for Systems Engineers
Author(s) -
JeanPhilippe M.
Publication year - 2003
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2003.tb02714.x
Subject(s) - troubleshooting , bayes' theorem , bayesian network , computer science , bayesian programming , bayesian probability , artificial intelligence , machine learning , software engineering , industrial engineering , engineering , bayes factor , operating system
Amongst many other considerations, Systems Engineering is based on the capability to predict and control the behaviour of a system. The Bayesian networks method is a technique that uses the theorem of Reverend Thomas BAYES, as established about 250 years ago and as developed by the great mathematician LAPLACE. Dealing with the BAYES theorem is usually reserved to mathematicians, since its application quickly requests a high level of mathematical awareness. Most systems engineers have had some courses on BAYES theorem during their studies, but they cannot envision any use of this rusty knowledge in their daily work. The goal of this paper is to describe four practical uses of Bayesian networks, which can be understood by the “regular” Systems Engineer: Selecting a design and making trade‐offs Controlling the system behaviour Assisting the troubleshooting during integration Facilitating system maintenance