Course detail
Advanced Methods of Decission
FP-IpmrKAcad. year: 2022/2023
The content of the subject is to make students familiar with the methods of analyses and simulation techniques (fuzzy logic, artificial neural networks, and genetic algorithms) by the way of explanation of the principles of these theories and their resulting applications in managerial practice.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Learning outcomes of the course unit
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
The exam will be classified according ECTS. The way of implementation is in the form of test with in the range 0-20 points. A-20-19;B18-17;C16-15;D14-13;E12-;F10-0.
Course curriculum
2. Fuzzy logic - theory
3. Fuzzy logic + application - Excel
4. Fuzzy logic - MATLAB application
5. Artificial neural networks - theory
6. Artificial neural networks + MATLAB applications
7. Genetic algorithms - theory
8. Genetic algorithms + MATLAB applications
9. Chaos theory
10. Datamining
11. Prediction, capital market
12. Production and risk management
13. Decision making
Work placements
Aims
1. Introduction
2. Fuzzy logic - theory
3. Fuzzy logic + application - Excel
4. Fuzzy logic - MATLAB application
5. Artificial neural networks - theory
6. Artificial neural networks + MATLAB applications
7. Genetic algorithms - theory
8. Genetic algorithms + MATLAB applications
9. Chaos theory
10. Datamining
11. Prediction, capital market
12. Production and risk management
13. Decision making
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
DOSTÁL, P. Pokročilé metody analýz a modelování v podnikatelství a veřejné správě, CERM, 2008, 430s, ISBN 978-80-7204-605-8.
DOSTÁL, P, RAIS, K., SOJKA, Z.: Pokročilé metody manažerského rozhodování, Praha Grada, 2005., ISBN 80-247-1338-1.
THE MATHWORKS. MATLAB – User’s Guide, The MathWorks, Inc., 2011.
Recommended reading
DAVIS,L. Handbook of Genetic Algorithms, Int. Thomson Com. Press, 1991, 385 s., ISBN 1-850-32825-0
GATELY, E. Neural Network for Financial Forecasting, John Wiley & Sons Inc., 1996, 169 s., ISBN 0-471-11212-7
JANÍČEK, P. Systémové pojetí vybraných oborů pro techniky, CERM, Brno, 2007, 1234 s., ISBN 978-80-7204-554-9.
PETERS, E. Fractal Market Analysis, John Wiley & Sons Inc., 1994, 315 s., SBN 0-471-58524-6
REBEIRO,R.R., ZIMMERMANN,H.J. Soft Computing in Fin. Engineering, Spring Verlag Comp.,1999,509s.,ISBN3-7908-1173-4.
Elearning
Classification of course in study plans
- Programme MGR-IM-KS Master's 1 year of study, summer semester, compulsory
Type of course unit
Guided consultation in combined form of studies
Teacher / Lecturer
Syllabus
2. Fuzzy logic - terory
3. Fuzzy logic + application – Excel
4. Fuzzy logic – application Matlab
5. Artificial neural network - teory
6. Artificial neural network + applications Matlab
7. Genetic algorithms - theory
8. Genetic algorithms + aplikace Matlab
9. Theory of chaos
10. Datamining
11. Time series, prediction, capital markets
12. Production control, risk management
13. Decision making
Elearning