Course detail
Advanced Methods of Analyses and Simulation
ÚSI-RSPMOAcad. year: 2024/2025
The content of the subject “Advanced Methods of Analysis and Simulation” familiarises students with some non-standard advanced analysis methods and modelling techniques developed in order to support corporate decision-making. It focuses on issues present in the field of risk engineering via the explanation of theoretical principles, and involves students in learning to work with such theories, and their applications.
Language of instruction
Czech
Number of ECTS credits
4
Mode of study
Not applicable.
Guarantor
Department
Entry knowledge
Knowledge from areas of mathematics (linear algebra, vectors, functional analysis, matrix operations) and statistics (analysis of time series, regression analysis, the use of statistical methods in economics).
Rules for evaluation and completion of the course
Attendance: 80% face-to face tuition, 20% distance learning.
Attendance in seminars will be checked - students must achieve at least 75% attendance in seminars.
Absence from seminars can be compensated for via a special assignment or test.
Attendance in seminars will be checked - students must achieve at least 75% attendance in seminars.
Absence from seminars can be compensated for via a special assignment or test.
Aims
The aim of the course is to make students familiar with analysis methods and simulation techniques (fuzzy logic, artificial neural networks, and genetic algorithms) via the explanation of the principles of these theories and their resulting applications in corporate decision-making, with a focus on the issues of risk management.
The knowledge and skills obtained from the course will enable students to apply a high-quality and modern approach to analysis and simulation (in the state and private sectors of the economy, organizations, firms, companies, banks, etc.) in order to support corporate decision-making, with a focus on the issues of risk management.
The knowledge and skills obtained from the course will enable students to apply a high-quality and modern approach to analysis and simulation (in the state and private sectors of the economy, organizations, firms, companies, banks, etc.) in order to support corporate decision-making, with a focus on the issues of risk management.
Study aids
Not applicable.
Prerequisites and corequisites
Not applicable.
Basic literature
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. 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., SOJKA, Z. Financial Risk management, Zlín 2008, 80s., ISBN 978-80-7318-772-9.
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., SOJKA, Z. Financial Risk management, Zlín 2008, 80s., ISBN 978-80-7318-772-9.
Recommended reading
ALTROCK,C. Fuzzy Logic &Neurofuzzy, Book & Cd Edition, 1996, 375 s., ISBN 0-13-591512-0
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.
DAVIS,L. Handbook of Genetic Algorithms, Int. Thomson Com. Press, 1991, 385 s., ISBN 1-850-32825-0
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.
GATELY, E. Neural Network for Financial Forecasting, John Wiley & Sons Inc., 1996, 169 s., ISBN 0-471-11212-7
Matlab The MathWorks Inc., US, 2017
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.
SMEJKAL,V., RAIS, K. Řízení rizik ve firmách a jiných organizacích, Grada, Publishing.,a.s. Grada, Praha, 2006.
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.
DAVIS,L. Handbook of Genetic Algorithms, Int. Thomson Com. Press, 1991, 385 s., ISBN 1-850-32825-0
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.
GATELY, E. Neural Network for Financial Forecasting, John Wiley & Sons Inc., 1996, 169 s., ISBN 0-471-11212-7
Matlab The MathWorks Inc., US, 2017
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.
SMEJKAL,V., RAIS, K. Řízení rizik ve firmách a jiných organizacích, Grada, Publishing.,a.s. Grada, Praha, 2006.
Elearning
eLearning: currently opened course
Classification of course in study plans
Type of course unit
Lecture
26 hod., optionally
Teacher / Lecturer
Syllabus
1. Introduction and definition of the subject "Advanced methods of analysis and simulation”
2. Identification of basic terms in the area of analysis
3. Identification of the basic terms and rules of fuzzy logic, the creation 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 simulating prediction by means of fuzzy logic, neural networks and genetic algorithms
10. Introduction to chaos theory and its possible usage in risk management
11. The usage of software for solving problems
12. Introduction to issues related to simulation
13. Presentation of applications of the usage of simulation in risk management
2. Identification of basic terms in the area of analysis
3. Identification of the basic terms and rules of fuzzy logic, the creation 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 simulating prediction by means of fuzzy logic, neural networks and genetic algorithms
10. Introduction to chaos theory and its possible usage in risk management
11. The usage of software for solving problems
12. Introduction to issues related to simulation
13. Presentation of applications of the usage of simulation in risk management
Elearning
eLearning: currently opened course