Course detail
Advanced Methods of Decission
FP-IpmrPAcad. year: 2024/2025
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
Entry knowledge
Rules for evaluation and completion of the course
The exam is a form of online test. Test is classified according to ECTS. The test has a score in the range of 0-20 points. A-20-19;B18-17;C16-15;D14-13;E12-10;F9-0.
To pass the exam, it is necessary to submit a seminar paper in the range of 8-12 pages with an individual focus of the student on practical issues, leading to a solution using the theory of fuzzy logic or artificial neural networks or genetic algorithms and its successful defense.
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
The obtained knowledge and skills of the subject will enable the graduates the top and modern access in the processes of analyses and simulation in the national economy and private sector, organizations, firms, companies, banks, etc., especially in managerial, but also in economical and financial sphere.
Study aids
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. (CS)
DOSTÁL, P, RAIS, K., SOJKA, Z.: Pokročilé metody manažerského rozhodování, Praha Grada, 2005., ISBN 80-247-1338-1. (CS)
THE MATHWORKS. MATLAB – User’s Guide, The MathWorks, Inc., 2021. (EN)
Recommended reading
DAVIS,L. Handbook of Genetic Algorithms, Int. Thomson Com. Press, 1991, 385 s., ISBN 1-850-32825-0 (EN)
GATELY, E. Neural Network for Financial Forecasting, John Wiley & Sons Inc., 1996, 169 s., ISBN 0-471-11212-7 (EN)
JANÍČEK, P. Systémové pojetí vybraných oborů pro techniky, CERM, Brno, 2007, 1234 s., ISBN 978-80-7204-554-9. (CS)
PETERS, E. Fractal Market Analysis, John Wiley & Sons Inc., 1994, 315 s., SBN 0-471-58524-6 (EN)
REBEIRO,R.R., ZIMMERMANN,H.J. Soft Computing in Fin. Engineering, Spring Verlag Comp.,1999,509s.,ISBN3-7908-1173-4. (EN)
Elearning
Classification of course in study plans
- Programme MGR-IM Master's 1 year of study, summer semester, compulsory
Type of course unit
Lecture
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
Exercise
Teacher / Lecturer
Syllabus
- Introduction
- Fuzzy logic I – Excel
- Fuzzy logic II – Excel
- Introduction to MATLAB
- Fuzzy logic IV – MATLAB
- Fuzzy logic in MATLAB
- Neural networks
- Genetic algorithms
- Consultation on seminar work
- Presentation of seminar work I
- Presentation of seminar work II
- Consultation
13.Consultation
Elearning