Title :
Approximate sensitivity analysis for acyclic Markov reliability models
Author :
Ou, Yong ; Dugan, Joanne Bechta
Author_Institution :
Dept. of Electr. & Comput. Eng., Virginia Univ., Charlottesville, VA, USA
fDate :
6/1/2003 12:00:00 AM
Abstract :
Acyclic Markov chains are frequently used for reliability analysis of nonmaintained mission-critical computer-based systems. Since traditional sensitivity (or importance) analysis using Markov chains can be computationally expensive, an approximate approach is presented which is easy to compute and which performs quite well in test cases. This approach is presented in terms of a Markov chain which is used for solving a dynamic fault-tree, but the approach applies to any acyclic Markov reliability model.
Keywords :
Markov processes; fault trees; reliability theory; sensitivity analysis; Markov chain; acyclic Markov reliability models; approximate sensitivity analysis; dynamic fault tree; importance analysis; nonmaintained mission-critical computer-based systems; reliability; Fault trees; Mission critical systems; Performance analysis; Performance evaluation; Power system modeling; Probability; Reliability; Sensitivity analysis; Testing; Vehicle dynamics;
Journal_Title :
Reliability, IEEE Transactions on
DOI :
10.1109/TR.2003.809657