Course detail

Advanced Methods of Decission

FP-IpmrPAcad. 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

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

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, and exercises that promote the practical knowledge of the subject presented in the lectures.

Assesment methods and criteria linked to learning outcomes

The credit will be granted in case of an active participation in trainings and handing in the final assignment, in case of need the written test. 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

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

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.

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

The participation in lectures is not checked. The participation in trainings is systematically 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. (EN)
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

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

  • Programme MGR-SI Master's

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

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

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 hod., optionally

Teacher / Lecturer

Syllabus

  1. Introduction
  2. Fuzzy logic I - Excel
  3. Fuzzy logic II - Excel
  4. Preparation of seminar work I
  5. Introduction to MATLAB
  6. Fuzzy logic IV - MATLAB
  7. Fuzzy logic V - MATLAB
  8. Preparation of seminar work II
  9. Neural networks
  10. Genetic algorithms
  11. Preparation of seminar work III
  12. Presentation of seminar paper I
  13. Presentation of seminar work II

Elearning