Course detail

Advanced Methods of Analyses and Simulation

FIT-PMMAcad. 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.

Learning outcomes of the course unit

The obtained knowledge and skills of the subject will enable the graduates the top and modern access in the processes of analyses and simulation in the national economy and private sector, organizations, firms, companies, banks, etc., especially in managerial, but also in economical and financial sphere.

Prerequisites

The knowledge in the area of math (linear algebra, arrays, analyses of functions, operations with matrixes) statistics (analysis of time series, regression analyses, the use of statistical methods in economy), operational analysis (linear programming), financial analyses and planning (the analyses of profits and costs, cash flow, value and bankruptcy model).

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

  • DOSTÁL, P. Pokročilé metody analýz a modelování v podnikatelství a veřejné správě, CERM, 2008, 430s, ISBN 978-80-7204-605-8.
  • DOSTÁL, P.: Advanced Decision making in Business and Public Services, Akademické nakladatelství CERM, 2011 Brno,ISBN 978-80-7204-747-5.
  • 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.

  • 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.
  • JANÍČEK, P. Systémové pojetí vybraných oborů pro techniky, CERM, Brno, 2007, 1234 s., ISBN 978-80-7204-554-9.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Study evaluation is based on marks obtained for specified items. Minimimum number of marks to pass is 50.

Language of instruction

Czech

Work placements

Not applicable.

Course curriculum

    Syllabus of lectures:
    1. Fuzzy logic (FL): To be familiar with the basic notions and fuzzy logic rules, creation of models. The presentation of cases of application of fuzzy logic in decision making processes e.g. managerial and investment decision making, prediction, etc. 
    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: 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. 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 
    6. Simulation: The presentation of the notion system and its identification and simulation. The description of the use of FL, ANN and GA during the process of simulation of decision making processes in enterprise sphere.
    7. 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.
    8. Stock market: The presentation of the notion stock market. The description of the use of FL, UNS a GA on stock market.
    9. Decision making: The presentation of the notion decision making. The description of the use of FL, UNS a GA for decision making processes.
    10. Summary

Aims

The aim of the course is to get acquainted with some advanced and non-standard methods of analysis and simulation techniques in economy and finance by the method of explanation of these theories, to become familiar with these theories and their use.

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

The participation in lectures is not checked. The participation in trainings is compulsory and is systematically checked. The students are supposed to excuse for their absence. The teacher judges the reason of excuse. The way of substitution of a missed training will be set by the teacher individually.

Classification of course in study plans

  • Programme IT-MGR-2 Master's

    branch MMI , any year of study, summer semester, 4 credits, compulsory-optional

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Syllabus


  1. Fuzzy logic (FL): To be familiar with the basic notions and fuzzy logic rules, creation of models. The presentation of cases of application of fuzzy logic in decision making processes e.g. managerial and investment decision making, prediction, etc. 
  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: 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. 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 
  6. Simulation: The presentation of the notion system and its identification and simulation. The description of the use of FL, ANN and GA during the process of simulation of decision making processes in enterprise sphere.
  7. 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.
  8. Stock market: The presentation of the notion stock market. The description of the use of FL, UNS a GA on stock market.
  9. Decision making: The presentation of the notion decision making. The description of the use of FL, UNS a GA for decision making processes.
  10. Summary

Fundamentals seminar

13 hours, optionally

Teacher / Lecturer

eLearning