Course detail

Advanced Methods of Decission

FP-IpmrPAcad. year: 2023/2024

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

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

prof. Ing. Petr Dostál, CSc.

Department

Institute of Informatics (ÚI)

Entry knowledge

Not applicable.

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

The aim of the course is to get acquainted with some advanced and non-standard methods of analysis and simulation techniques in economy and finance by the method of explanation of these theories, to become familiar with these theories and their use.

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

Not applicable.

Prerequisites and corequisites

Not applicable.

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.: Advanced Decision making in Business and Public Services, Akademické nakladatelství CERM, 2011 Brno,ISBN 978-80-7204-747-5. (EN)
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

ALTROCK,C. Fuzzy Logic &Neurofuzzy, Book & Cd Edition, 1996, 375 s., ISBN 0-13-591512-0 (EN)
GATELY, E. Neural Network for Financial Forecasting, John Wiley & Sons Inc., 1996, 169 s., ISBN 0-471-11212-7 (EN)
DAVIS,L. Handbook of Genetic Algorithms, Int. Thomson Com. Press, 1991, 385 s., ISBN 1-850-32825-0 (EN)
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)
JANÍČEK, P. Systémové pojetí vybraných oborů pro techniky, CERM, Brno, 2007, 1234 s., ISBN 978-80-7204-554-9. (CS)

eLearning

eLearning: currently opened course

Classification of course in study plans

  • Programme MGR-IM Master's, 1. year of study, summer semester, compulsory

  • Programme MGR-SI Master's

    branch MGR-IM , 1. year of study, summer semester, compulsory

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

prof. Ing. Petr Dostál, CSc.

Syllabus

1. Introduction
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

26 hours, compulsory

Teacher / Lecturer

Ing. et Ing. Zuzana Janková, Ph.D.

Syllabus

1. Introduction
2. Fuzzy logic – Excel + Assignment Ia
3. Fuzzy logic – Matlab I.
4. Fuzzy logic – Matlab II.
5. Fuzzy logic – Assignment Ib - Matlab
6. Fuzzy logic – Assignment IIa
7. Neural networks I.
8. Neural networks II.
9. Genetic algorithms I.
10. Genetic algorithms II.
11. Theory of chaos, Assignment IIb
12. Defence of Assignment
13. Credit

eLearning

eLearning: currently opened course