Course detail

Advanced Methods of Analyses and Simulation

ÚSI-2SBPAAcad. year: 2017/2018

The content of the subject "Advanced Methods of Analyses and Simulation" is to get acquainted with some advanced and non-standard methods of analysis and simulation techniques as a support of decision making in business focussed on problems of risk management by the method of explanation of these theories, to become familiar with these theories and their use.

Language of instruction

Czech

Number of ECTS credits

4

Mode of study

Not applicable.

Learning outcomes of the course unit

The obtained knowledge and skills of the subject will enable the graduates fine and modern access in the processes of analyses and simulation (in the national economy and private sector, organizations, firms, companies, banks, etc.) in order to support decision making in business focussed on problems of risk management.

Prerequisites

Knowledge from the mathematical sector (linear algebra, arrays, analyses of functions, operations with matrixes), statistics (analysis of time series, regression analyses, the use of statistical methods in economy), risk management.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Teaching is carried out through lectures and seminars. Lectures consist of interpretations of basic principles, methodology of given discipline, problems and their exemplary solutions. Seminars particularly support practical mastery of subject matter presented in lectures or assigned for individual study with the active participation of students.

Assesment methods and criteria linked to learning outcomes

The credit will be granted in case of active participation in trainings, and handing in the final assignment and the final 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 and neural network or genetic algorithms.

Course curriculum

1. Introduction and definition of subject "Advanced methods of analyses and simulation
2. Identification of basic terms in area of analyses
3. Identification of basic terms and fuzzy logic rules, build-up of models
4. Presentation of case studies of the use of fuzzy logic in risk management
5. Identification of basic terms in the area of artificial neural networks
6. Presentation of case studies of the use of artificial neural networks in risk management
7. Identification of basic terms in the area of genetic algorithms
8. Presentation of case studies of the use of genetic algorithms in risk management
9. Methods of simulation of prediction by means of fuzzy logic, neural networks and genetic algorithms
10. Introduction to theory of chaos and possible usage in risk management
11. The usage of software means for solving problems
12. Introduction to problems of simulation
13. Presentation of applications of the usage of simulation in risk management

Work placements

Not applicable.

Aims

The aim of the course 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 decision making in business focussed to problems of risk management.

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

Attendance form: 80% face-to face, 20% distance learning.
Attendance in seminars will be checked, a student has to fulfil at least 75% attendance in seminars.
Absence in seminars could be recompense with a special assignment or with a special exam test.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

DOSTÁL, P. Pokročilé metody rozhodování v podnikatelství a veřejné správě. Brno: CERM Akademické nakladatelství, 2012. 718 p. ISBN 978-80-7204-798-7, e-ISBN 978-80-7204-799-4.
DOSTÁL, P. Advanced Decision Making in Business and Public Services. Brno: CERM Akademické nakladatelství, 2013. 168 p. ISBN: 978-80-7204-747-5
DOSTÁL, P., SOJKA, Z. Financial Risk management, Zlín 2008, 80s., ISBN 978-80-7318-772-9.

Recommended reading

DOSTÁL, P. The Use of Optimization Methods in Business and Public Services. In Zelinka, I., Snášel, V., Abraham, A. Handbook of Optimization, USA: Springer, 2012. ISBN 978-3-642-30503-0.
BROZ, Z., DOSTÁL, P. Multilingual dictionary of artificial intelligence. Brno: CERM Akademické nakladatelství, 2012. 142 p. ISBN 978-80-7204-800-7, e-ISBN 978-80-7204-801-4.
SMEJKAL,V., RAIS, K. Řízení rizik ve firmách a jiných organizacích, Grada, Publishing.,a.s. Grada, Praha, 2006.
ALTROCK,C. Fuzzy Logic &Neurofuzzy, Book & Cd Edition, 1996, 375 s., ISBN 0-13-591512-0
GATELY, E. Neural Network for Financial Forecasting, John Wiley & Sons Inc., 1996, 169 s., ISBN 0-471-11212-7
DAVIS,L. Handbook of Genetic Algorithms, Int. Thomson Com. Press, 1991, 385 s., ISBN 1-850-32825-0
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.

Classification of course in study plans

  • Programme MRzI Master's

    branch REZ , 1. year of study, summer semester, compulsory
    branch RSZ , 1. year of study, summer semester, compulsory
    branch RFI , 1. year of study, summer semester, compulsory
    branch RSK , 1. year of study, summer semester, compulsory
    branch RIS , 1. year of study, summer semester, compulsory
    branch RCH , 1. year of study, summer semester, compulsory

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Syllabus

1. Introduction and definition of subject "Advanced methods of analyses and simulation
2. Identification of basic terms in area of analyses
3. Identification of basic terms and fuzzy logic rules, build-up of models
4. Presentation of case studies of the use of fuzzy logic in risk management
5. Identification of basic terms in the area of artificial neural networks
6. Presentation of case studies of the use of artificial neural networks in risk management
7. Identification of basic terms in the area of genetic algorithms
8. Presentation of case studies of the use of genetic algorithms in risk management
9. Methods of simulation of prediction by means of fuzzy logic, neural networks and genetic algorithms
10. Introduction to theory of chaos and possible usage in risk management
11. The usage of software means for solving problems
12. Introduction to problems of simulation
13. Presentation of applications of modeling in risk management

Exercise

26 hours, compulsory

Teacher / Lecturer