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Approximate mean value analysis for stochastic marked graphs
DOI:10.1109/32.541436.png)
Abstract
En 中文
An iterative technique for the computation of approximate performance indices of a class of stochastic Petri nets models is presented. The proposed technique is derived from the mean value analysis algorithm for product form solution stochastic Petri nets. in this paper, we apply the approximation technique to stochastic marked graphs; In principle, the proposed technique can be used for other stochastic Petri net subclasses in the paper, some of these possible applications are presented. Several examples are presented in order to validate the approximate results.
Keywords:
stochastic Petri nets
marked graphs
computational algorithms
approximate mean value analysis algorithm
approximation techniques
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