Séminaire Mathématique de Béjaia
Volume 16, Numéro 1, Pages 115-115
2018-12-31
Polynomial Chaos Expansion For Uncertainty Propagation In Unreliable Queuing Models
Authors : Bachi Katia . Chauviere Cédric . Djellout Hacène . Abbas Karim .
Abstract
In queuing systems, an interest measures are evaluated at the fixed parameters values. However, these parameters are uncontrollable inputs, and generally estimated from few experimental observations, or only by guessing. The lack of information on the input parameters is translated in this work by a random variable. As result of the uncertainties in model input, the model output is considered also uncertain and supposed to be random variable. In this work, we develop a numerical approach to propagate the parametric uncertainty on the queuing systems via the approach based on the polynomial chaos expansion. Indeed, our interest is focused particularly on the output measures affected by the uncertainty of the input parameters, thereby, the interest measures are considered as function of the uncontrollable parameters. This approach allows, on the one hand, the approximation of the interest measures, on the other hand, the uncertainty analysis by the computation of expected value, and variance of the output measures. Numerical results are presented and compared to the corresponding Monte-Carlo simulation.
Keywords
Unreliable queuing model; Epistemic uncertainty; Chaos expansions; Orthogonal polynomial.
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