Course: Simulation and Modelling

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Course title Simulation and Modelling
Course code FES/DSIM
Organizational form of instruction Lecture
Level of course Doctoral
Year of study not specified
Semester Winter and summer
Number of ECTS credits 10
Language of instruction Czech
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Antlová Klára, doc. Ing. Ph.D.
  • Hubálovský Štěpán, doc. RNDr. Ph.D.
Course content
Complex systems and cybernetic concepts. Soft and Hard systems. Nonlinear control systems, adaptive control systems, optimization options. Multi-criteria decision analysis. Decision making using the "Rule-Based Reasoning", "Case-Based Reasoning" and "Rough Sets Theory."

Learning activities and teaching methods
unspecified, Methods of individual activities
Learning outcomes
The aim of the course it to meet students with basic knowledge and modern approaches to system analyses and syntheses, to provide students with essential attributes of static and dynamic systems, with proposals of their mathematic models and with transformation of mathematic models into simulation programmes.g
PhD students will be able to use the system approach for problem formulation, decomposition and formalization. They are able to design and analyze models of different classes of complex systems.
Prerequisites
unspecified

Assessment methods and criteria
Oral examination, Creative work analysis

Students will process a work independently within the scope of a research paper in this course. The topic of the paper is in relation to the specific topic of the dissertation thesis.
Recommended literature
  • Carlsson, Christer. Fuzzy reasoning in decision making and optimization. Heidelberg: Physica-Verlag, 2002. ISBN 3-7908-1428-8.
  • Doumpos, Michael. Multicriteria decision aid and artificial intelligence : links, theory and applications. Chichester: John Wiley & Sons, 2013. ISBN 978-1-119-97639-4.
  • Kou, Gang. Data processing for the AHP/ANP. Berlin: Springer-Verlag, 2013. ISBN 978-3-642-29212-5.
  • Pal, Sankar K. Foundations of soft case-based reasoning. Hoboken: Wiley-Interscience, 2004. ISBN 0-471-08635-5.
  • Saaty, T. L. The Analytic Hierarchy Process. New York: McGraw-Hill International Book Company, 1980. ISBN 0070543712.
  • Shinners, Stanley M. Modern control system theory and design. New York: John Wiley & Sons, 1998. ISBN 0-471-24906-8.
  • Slowinski R. (ed.). Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory. Dordrecht: Kluwer Academic Publisher, 1992.
  • Turban, Efraim. Decision support and business inteligence systems. Upper Saddle River: Pearson Prentice Hall, 2007. ISBN 0-13-198660-0.
  • Turban, Efraim. Decision support systems and intelligent systems. Upper Saddle River: Pearson Education, 2005. ISBN 0-13-046106-7.
  • Watson, Ian D. Applying case-based reasoning : techniques for enterprise systems. San Francisco: Morgan Kaufmann, 1997. ISBN 1-55860-462-6.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester