Course detail
Advanced Methods of Analyses and Simulation
ÚSI-2SBPAAcad. year: 2018/2019
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
Number of ECTS credits
Mode of study
Guarantor
Department
Learning outcomes of the course unit
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
1) Active participation in the exercises, i.e. processing of at least 4 of the 5 thematic tasks in the individual exercises (1. FL Excel, 2. FL MATLAB, 3. NN, 4. GA, 5. theory of chaos).
2) At least 5 points from the written semester project (max. 10 points). The scope of the project will be about 8 - 12 pages with an individual focus of the student on practical problems leading to the solution using fuzzy logic theory, artificial neural networks or genetic algorithms. Details of the project will be presented at the first exercise and the work must be submitted by the end of the 10th semester week.
The exam is classified according to ECTS. It is in written form of closed questions with a score of 0-20 points. A: 20-19; B: 18-17; C: 16-15; D: 14-13; E: 12-10; F: 9-0.
Course curriculum
2. Artificial neural networks (ANN): To be familiar with the basic notions in the area of artificial neural networks, presentation of the notation perceptron, multilayer neural network and their parameters. The applications cover investment decision making, estimations of the price of products, real properties, evaluation of value of client, etc.
3. Genetic algorithms (GA): To be familiar with the principles of genetics, the analogy between nature and math description that enables the solution of decision making of problems. The use in the area of optimization of wide spectrum of problems is mentioned - the optimization of investment strategy, production control, cutting plans, curve fitting, the solution of traveling salesman, cluster analyses, etc.
4. Chaos theory (CH): The theory deals with the possibilities of better description of economic phenomena than the classical methods do. The notion chaos, order and fractal are clarified, the use of this theory to determinate the level of chaos of measured and watched system is mentioned
5. The use of mentioned theories in datamining, prediction, production control, risk management and decision making.
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
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., SOJKA, Z. Financial Risk management, Zlín 2008, 80s., ISBN 978-80-7318-772-9.
Recommended reading
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
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.
Classification of course in study plans
- Programme MRzI Master's
branch RIS , 1 year of study, summer semester, compulsory
branch RCH , 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 RSZ , 1 year of study, summer semester, compulsory
branch REZ , 1 year of study, summer semester, compulsory
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
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
Teacher / Lecturer
Syllabus
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