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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 Compulsory-optional
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, Ch., Fulle, R. Fuzzy Reasoning in Decision Making and Optimization. Physica Verl., New York, 2002..
  • Doumpos, M., Grigoroudis, E. (eds.). Multicriteria Decision Aid and Artificial inteligence. Links, Theory and Applications. John Wiley and Sons, Inc., West Sussex, 2013..
  • Kou, G., Ergu, D., Peng, Y., Shi, Y. Data Processing for the AHP/ANP. Springer, Heidelberg, 2013..
  • Pal, S. K., Shiu, S. C. K. Foundation of Soft Case-Based Reasoning. John Wiley and Sons, Inc., New Persey, 2004..
  • SAATY, T. L. The Analytic Hierarchy Process. New York : McGraw-Hill International Book Company, 1980. ISBN 0070543712.
  • SHINNERS, S. M. Modern Control System Theory and Design. NJ : John Wiley and Sons, 1998.
  • Slowinski R. (ed.). Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory. Kluwer Academic Publisher, Dordrecht, 1992..
  • Turban, E., Aronson J. E., Liang, T. P., Aharda, R. Decision Support Systems and Business Intelligent Systems. 8th ed., Pearson Education, Inc., Upper Saddle River, 2007..
  • Turban, E., Aronson J. E., Liang, T. P. Decision Support Systems and Intelligent Systems. 7th ed., Pearson Prentice Hall, New Persey, 2005..
  • Watson, I. Applying Case-Based Reasoning: Techniques for Enterprise System. Morgan Kaufmann Publisher Inc., San Francisco, 1997..


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Economics and Administration Study plan (Version): Applied Informatics (2014) Category: Informatics courses - Recommended year of study:-, Recommended semester: -
Faculty: Faculty of Economics and Administration Study plan (Version): Applied Informatics (2014) Category: Informatics courses - Recommended year of study:-, Recommended semester: -
University of Pardubice, date of update: 03.06.2024 23:50.