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Lecturer(s)
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Course content
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Random process, basic types of random processes, point processes. Poisson's process. Spectral decomposition of the random processes. Modeling of the stochastic processes. Markov´s processes, Markov´s chains. Queuing theory, basic terms, Kendall's classification, queues regimes. System M/M/n, Non- Markov´s queuing systems - M/D/1, M/G/1, M/Ek/1. Inventory theory - deterministic and stochastic models. Renewal theory - models s punished and backfiring elements.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming)
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Learning outcomes
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The target of the subject is to make the students acquainted with the selected topics from the random processes theory.
Student will be able to use these methods independently at the solution of the concrete examples from the branch of student´s doctoral study
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Prerequisites
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Knowledge of mathematics and probability is assumed in the range that is usual at the technical universities
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Assessment methods and criteria
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Oral examination
Student must be able to make the prescribed subject matted up from the theoretical and practical view.
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Recommended literature
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Hillier,S.F.,Lieberman,G.J. Introduction to Operations Research. McGraw Hill, 2001. ISBN 0-07-121744-4.
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Linda, Bohdan. Stochastické metody operačního výzkumu. Bratislava: Statis, 2004. ISBN 80-85659-33-6.
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Ventcelová,E.S. Teória prvděpodobnosti. Alfa, Bratislava, 1973.
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