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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 stochastics 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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Dupač, Václav. Pravděpodobnost a matematická statistika. Praha: Karolinum, 1999. ISBN 80-246-0009-9.
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Feller, W. An Introduction to Probability Theory and its Applications. New York: Wiley, 1966.
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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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Kubáčková, L. Náhodné funkce a jejich aplikace. Olomouc: Vydavatelství UP, 1997.
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Linda, Bohdan. Stochastické metody operačního výzkumu. Bratislava: Statis, 2004. ISBN 80-85659-33-6.
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Michálek, Jiří. Úvod do teorie náhodných procesů. Praha: Vydavatelství ČVUT, 2000. ISBN 80-01-02088-6.
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Norris, J. Markov chains. Cambridge: University Press, 1998.
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Prášková, Zuzana. Základy náhodných procesů. Praha: Karolinum, 1998. ISBN 80-7184-688-0.
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