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Course: Methods of Artificial and Computational Intelligence in Regional Management

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Course title Methods of Artificial and Computational Intelligence in Regional Management
Course code FES/AMUV
Organizational form of instruction Lecture
Level of course Doctoral
Year of study not specified
Semester Winter and summer
Number of ECTS credits 8
Language of instruction English
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)
  • Olej Vladimír, prof. Ing. CSc.
Course content
Artificial and computational intelligence. Expert systems. Knowledge representation. Design diagnostic expert system by AND/OR graph and production rules. Design expert system with uncertainty. Synthesis and analysis of decision-making processes with uncertainty. Classification and prediction economic processes by fuzzy inference systems. Models of neural networks, classification and prediction. Evolution stochastic optimization algorithms. Neuro-fuzzy-genetic systems.

Learning activities and teaching methods
Monologic (reading, lecture, briefing)
Learning outcomes
The aim of the course is to provide basic knowledge in the area of artificial intelligence (programming language artificial intelligence, knowledge-based and expert systems, knowledge representation) and computational intelligence (fuzzy sets, neural network and evolution stochastic optimization algorithms) and the possibilities for its use in public administration and management.
The students should be able to design neuro-fuzzy systems and knowledge base for expert sytems.
Prerequisites
unspecified

Assessment methods and criteria
Oral examination

Completion and successful defense of project from the field of dissertation work.
Recommended literature
  • GHOSH A., TSUTSUI S. Advances in Evolutionary Computing. Theory and Applications.. A Springer-Verlag Company, Germany, 2003.
  • KELEMEN J., LIDAY M. Expertné systémy pre prax.. SOFA, Bratislava, 1996.
  • KUNCHEVA L. I. Fuzzy Classifier Design.. A Springer Verlag Company, Germany, 2000.
  • KVASNIČKA V. a kol. Evolučné algoritmy.. STU, Bratislava, 2000.
  • Kvasnička V. a kol. Úvod do teórie neurónových sietí. 1997, IRIS Bratislava.. IRIS, Bratislava, 1997.
  • NILSSON N. J. Artificial Intelligence: A New Synthesis.. Morgan Kaufmann, 1998. ISBN 1558604677.
  • OLEJ V. Modelovanie ekonomických procesov na báze výpočtovej inteligencie.. Miloš Vognar - M&V, Hradec Králové, 2003. ISBN 80-903024-9-1.
  • RUSSEL S., NORVIG P. Artificial Intelligence. A Modern Approach.. Prentice Hall, Second Edition, New Jersey, 2003.
  • RUTKOWSKI L., KACPRZYK J. Advances in Soft Computing. Neural Networks and Soft Computing.. A Springer-Verlag Company, Germany, 2003.


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): Regional and Public Economics (2013) Category: Economy - Recommended year of study:-, Recommended semester: -
Faculty: Faculty of Economics and Administration Study plan (Version): Regional and Public Economics (2013) Category: Economy - Recommended year of study:-, Recommended semester: -
University of Pardubice, date of update: 28.05.2024 23:50.