Titlebook: Numerical Methods for Solving Discrete Event Systems; With Applications to Winfried Grassmann,Javad Tavakoli Textbook 2022 The Editor(s) (i

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書目名稱Numerical Methods for Solving Discrete Event Systems影響因子(影響力)




書目名稱Numerical Methods for Solving Discrete Event Systems影響因子(影響力)學(xué)科排名




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書目名稱Numerical Methods for Solving Discrete Event Systems網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Numerical Methods for Solving Discrete Event Systems被引頻次




書目名稱Numerical Methods for Solving Discrete Event Systems被引頻次學(xué)科排名




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書目名稱Numerical Methods for Solving Discrete Event Systems讀者反饋




書目名稱Numerical Methods for Solving Discrete Event Systems讀者反饋學(xué)科排名

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Numerical Methods for Solving Discrete Event Systems978-3-031-10082-6Series ISSN 2730-650X Series E-ISSN 2730-6518

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https://doi.org/10.1007/978-3-031-10082-6Discrete event systems; Markov chains; Queueing; Inventory control; Numerical methods; Matrix analytic me

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Moving toward the Statistical Equilibrium,d if they exist, whether or not they depend on the initial state. These are the questions addressed in this chapter. The tools to resolve these questions include the classification of states, as well as the characterization of transient solutions by eigenvalues.

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Equilibrium Solutions of Markov Chains and Related Topics,fference between the equilibrium equations of DTMCs and CTMCs. In particular, we discuss the state elimination method, a variant of Gaussian elimination that has probabilistic interpretation. This then leads to the fundamental matrix and its use. Iterative methods are also described, and illustrated by examples.

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Reducing the Supplementary State Space Through Embedding,te variables. Two types of embedding points are discussed: One can embed the process at the points where any of the events happens, or one can select a specific event type, such as arrivals, and use these as embedding points.