Interval-type and affine arithmetic-type techniques for handling uncertainty in expert systems
Journal of Computational and Applied Mathematics - Special issue: Scientific computing, computer arithmetic, and validated numerics (SCAN 2004)
Introduction to Interval Analysis
Introduction to Interval Analysis
Uncertainty handling in quantitative BDD-based fault-tree analysis by interval computation
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
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In many real-life applications (e.g., in aircraft maintenance), we need to estimate the probability of failure of a complex system (such as an aircraft as a whole or one of its subsystems). Complex systems are usually built with redundancy allowing them to withstand the failure of a small number of components. In this paper, we assume that we know the structure of the system, and, as a result, for each possible set of failed components, we can tell whether this set will lead to a system failure. For each component A, we know the probability P(A) of its failure with some uncertainty: e.g., we know the lower and upper bounds $\underline P(A)$ and $\overline P(A)$ for this probability. Usually, it is assumed that failures of different components are independent events. Our objective is to use all this information to estimate the probability of failure of the entire the complex system. In this paper, we describe a new efficient method for such estimation based on Cauchy deviates.