Course detail

Advanced Methods of Analyses and Simulation

ÚSI-RSPMOAcad. year: 2020/2021

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.

Learning outcomes of the course unit

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.

Prerequisites

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).

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

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.
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.
Matlab The MathWorks Inc., US, 2017

Planned learning activities and teaching methods

Tuition takes place via lectures and seminars. The lectures focus on the explanation of basic principles, the methods of the given discipline, problems and example solutions. The seminars mainly support practical mastery of the subject matter presented in lectures or assigned for individual study with the active participation of students.

Assesment methods and criteria linked to learning outcomes

Zkouška: písemný test
Cvičení: Účast na cvičeních (absence na cvičeních může být nahrazena náhradními úkoly či písemnými testy). Odevzdání seminární práce.

Language of instruction

Czech

Work placements

Not applicable.

Course curriculum

Lectures:
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

Seminars:
1. Introduction
2. Fuzzy logic I – Excel + Assignment a
3. Fuzzy logic II – Excel + Assignment b
4. Fuzzy logic III – MATLAB
5. Fuzzy logic IV – MATLAB + Assignment c
6. Fuzzy logic – MATLAB + Assignment d
7. Defence of Assignment
8. Defence of Assignment
9. Neural networks I – MATLAB
10 Neural networks II – MATLAB
11. Genetic algorithms I – MATLAB
12. Genetic algorithms II - – MATLAB
13. Credit

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.

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

Optional distance or contact lecture according to the regulation.
Attendance at seminars is mandatory online or contact according to the regulations.
Absences from seminars can be replaced by substitute tasks or written tests.

Classification of course in study plans

  • Programme RRTES_P Master's

    specialization RRES , 1. year of study, summer semester, 4 credits, compulsory
    specialization RRTS , 1. year of study, summer semester, 4 credits, compulsory

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Exercise

26 hours, compulsory

Teacher / Lecturer

eLearning