Course detail
Advanced Methods of Analyses and Simulation
FP-FpmamKAcad. year: 2017/2018
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
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
Course curriculum
3,4. 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.
5,6. 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.
7. Chaos theory: 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
8. Data mining: The notion data mining, the definition of aims, the selection of methods of simulation, sources and preparation of data, creation of models, their verification, evaluation, implementation and maintenance are mentioned there. The presentation of the cases of the use for strategy of cooperation with customer, direct mailing, etc.
9. Simulation: The presentation of the notion simulation and its identification and simulation. The use of FL, UNS a GA as a mean of simulation.
10. Prediction: The presentation of methods of prediction of time series by means of FL, ANN and GA and their use for prediction of future development of various economic values in practice.
11. Stock market: The presentation of the notion stock market. The description of the use of FL, UNS a GA on stock market.
12. Decision making: The presentation of the notion decision making. The description of the use of FL, UNS a GA for decision making processes.
13. Summary
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 analýz a modelování v podnikatelství a veřejné správě, Akademické nakladatelství CERM, 2008 Brno,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
DOSTÁL, P. The Use of Soft Computing in Management. In Vasant, P. Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications USA: IGI Globe, 2013. DOI: 10.4018/978-1-4666-4450-2, ISBN13: 9781466644502, ISBN10: 1466644508, EISBN13: 9781466644519.
Classification of course in study plans
- Programme MGR-KS Master's
branch MGR-UFRP-KS , 2 year of study, winter semester, elective
Type of course unit
Guided consultation in combined form of studies
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