Course detail

Advanced Methods of Decission

FP-IpmrKAcad. year: 2021/2022

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)

Learning outcomes of the course unit

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.

Prerequisites

Not applicable.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

The course contains lectures that explain basic principles, problems and methodology of the discipline.

Assesment methods and criteria linked to learning outcomes

The seminar work wiil be required  for the credit. The work will range approximately from 8 to 12 pages concentrating on individual problem from practice leading to solution with the help of theory of fuzzy logic, artificial neural network or genetic algorithms.
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

Introduction, fuzzy logic - theory and practice
Artificial neural networks - theory and practice
Genetic algorithms - theory and practice, chaos theory
Datamining, prediction, capital market, production and risk management, decision making.

Work placements

Not applicable.

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 - fuzzy logic, artificial neural networks, genetic algorithms, chaos theory, datamining, pediction, capital market, production and risk management, decision making.

Specification of controlled education, way of implementation and compensation for absences

The participation in lectures is not checked.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

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

ALTROCK,C. Fuzzy Logic &Neurofuzzy, Book & Cd Edition, 1996, 375 s., ISBN 0-13-591512-0
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

eLearning: currently opened course

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

20 hod., 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

Elearning

eLearning: currently opened course