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Title: Choosing a heuristic for the “fault tree to binary decision diagram” conversion, using neural networks
Authors: Bartlett, L.M.
Andrews, J.D.
Keywords: Binary decision diagrams
Fault-tree analysis
Neural networks
Variable ordering heuristics
Issue Date: 2002
Publisher: © IEEE
Citation: BARTLETT, L.M. and ANDREWS, J.D., 2002. Choosing a heuristic for the “fault tree to binary decision diagram” conversion, using neural networks. IEEE Transactions on Reliability, 51(3), pp 344-349
Abstract: Fault-tree analysis is commonly used for risk assessment of industrial systems. Several computer packages are available to carry out the analysis. Despite its common usage there are associated limitations of the technique in terms of accuracy and efficiency when dealing with large fault-tree structures. The most recent approach to aid the analysis of the fault-tree diagram is the BDD (binary decision diagram). To use the BDD, the fault-tree structure needs to be converted into the BDD format. Converting the fault tree is relatively straightforward but requires that the basic events of the tree be ordered. This ordering is critical to the resulting size of the BDD, and ultimately affects the qualitative and quantitative performance and benefits of this technique. Several heuristic approaches were developed to produce an optimal ordering permutation for a specific tree. These heuristic approaches do not always yield a minimal BDD structure for all trees. There is no single heuristic that guarantees a minimal BDD for any fault-tree structure. This paper looks at a selection approach using a neural network to choose the best heuristic from a set of alternatives that will yield the smallest BDD and promote an efficient analysis. The set of possible selection choices are 6 alternative heuristics, and the prediction capacity produced was a 70% chance of the neural network choosing the best ordering heuristic from the set of 6 for the test set of given fault trees.
Description: This is a journal article. It was published in the journal, IEEE Transactions on Reliability [© IEEE] and the definitive version is also available at: http://ieeexplore.ieee.org. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
URI: https://dspace.lboro.ac.uk/2134/3741
ISSN: 0018-9529
Appears in Collections:Published Articles (Aeronautical and Automotive Engineering)

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