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- W4226060560 abstract "This chapter discusses the application of AA-based processing for computing reliable enclosures of transient state probabilities in Continuous Time Markov Chains. This method allows modeling the dynamic evolution of uncertain Markov Chains-based models through the solution of an equivalent set of deterministic ordinary differential equations, which can be solved with conventional techniques. By solving these equations, the parameters of the affine forms describing the state transient probabilities can be computed, and the bounds of the corresponding trajectories can be reliably estimated. The AA-based method is applied in the task of solving two case studies, with a different number of states, obtaining reliable enclosures of the “real” state trajectories estimated by a conventional sampling-based approach." @default.
- W4226060560 created "2022-05-05" @default.
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- W4226060560 date "2022-01-01" @default.
- W4226060560 modified "2023-09-26" @default.
- W4226060560 title "Uncertain power system reliability analysis" @default.
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- W4226060560 doi "https://doi.org/10.1016/b978-0-32-390502-2.00013-2" @default.
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