Předmět Advanced Decision Making (MUFU / PADME)

Na serveru studentino.cz naleznete nejrůznější studijní materiály: zápisky z přednášek nebo cvičení, vzorové testy, seminární práce, domácí úkoly a další z předmětu MUFU / PADME - Advanced Decision Making, Fakulta managementu a ekonomiky ve Zlíně, Univerzita Tomáše Bati ve Zlíně (UTB).

Materiál	Typ	Datum	Počet stažení

Obsah

- Fuzzy logic (FL): To be familiar with the basic notions and fuzzy logic rules, creation of models.- Fuzzy logic: The presentation of cases of application of fuzzy logic in decision making processes e.g. managerial and investment decision making, prediction etc.- 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.- Artificial neural networks: The applications cover investment decision making, estimations of the price of products, real properties, evaluation of value of client etc.- Evolution algorithms (EA): To be familiar with the principles of evolution algorithms, the analogy between nature and math description that enables the solution of decision making of problems, especially reduction of costs and increase of profit.- Evolution algorithms: It is mentioned the use in the area of optimization of wide spectrum of problems - the optimization of investment strategy, production control, cutting plans, curve fitting, the solution of traveling salesman, cluster analyses etc.- Chaos theory: The theory deals with the possibilities of better description of economic phenomenon, than the classical methods do. The notion chaos, order and fractal are clarified, it is mentioned the use of this theory to determinate the level of chaos of measured and watched system.- Prediction: The presentation of methods of prediction of time series by means of FL, ANN and EA and their use for prediction of future development of various economic values in practice.- Capital market: The use of the FL, ANN and EA on capital markets. It is mentioned the possible decision making process in the aim to achieve the optimum at purchase, sale or holding of shares, indexes, currency ratios or commodities. There are mentioned cases on the portfolio optimization, prediction etc.- Data mining: There are mentioned 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. The presentation of the cases of the use for strategy of cooperation with customer, direct mailing etc.- Simulation: The presentation of the notion systems and their identification and simulation. The description of the use of FL, ANN and EA during the process of simulation of decision making processes in enterprise sphere.- Risk management: The presentation of the notion risk and its evaluation. The use of FL, ANN and EA during the process of evaluation of risk in enterprise sphere.- Decision making process: The presentation of decision making processes with the purpose to achieve the optimum, where the FL, ANN and EA are used including their combinations. The conclusion sum up and evaluate the meaning of subject Advanced Decision Making in practice.

Získané způsobilosti

Students completing the course will be able to characterize the theory, methods of decision-making, including practical examples and applications of methods in practice.

Literatura

DOSTÁL, P. Advanced Decision Making Business and Public Services. Brno: CERM, 2011. Dostál, Petr. Advanced economic analyses. Vyd. 1. Brno : Akademické nakladatelství CERM, 2008. ISBN 978-80-214-3564-3.KLIR,G. J., YUAN, B. Fuzzy Sets and Fuzzy Logic : Theory and Applications. Upper Saddle River : Prentice Hall, 1995. ISBN 0131011715.Handbook of Genetic Algorithms. 1st ed. London : ITP, 1991. ISBN 1850328250.Gleick, James. Chaos : vznik nové vědy. Brno : Ando, 1996. ISBN 80-86047-04-0.HOGAN, T., DEMUTH, B. Neural Network Design. Boston : PWS Pub., 1996. ISBN 0534943322.Bose, N. K. Neural Network Fundamentals with Graphs, Algorithms, and Applications : Electrical and Computer Engineering Series. 5th ed. New York : McGraw-Hill, 1996. ISBN 70066183.GATELY, E. Neural Networks for Financial Forecasting. New York : Wiley, 1996. ISBN 0471112127.KAZABOV, KOZMA. Neuro-Fuzzy ? Techniques for Intelligent Information Systems. 1998. Alliev, A., Alliev, R. Soft Computing and Its Applications.

Požadavky

Způsob zakončení předmětu - klasifikovaný zápočetThe criteria for success in the Classified Course Credit will be:a) participation and activities in seminars (30%), b) comprehensive test (weight 40%), c) elaboration of assignment (30%) represented by case study solving the decision making problem by means of fuzzy logic with the help of MS Excel. This will be individually negotiable and approved. The result of a subject examination is expressed on a six-point scale: A "výborně" (i.e. "excellent"), B "velmi dobře" (i.e. "very good"), C "dobře" (i.e. "good"), D "uspokojivě" (i.e. "satisfactory"), E "dostatečně" (i.e. "sufficient"), F "nedostatečně" (i.e. "fail").

Garant

prof. Ing. Petr Dostál, CSc.

Vyučující

prof. Ing. Petr Dostál, CSc.prof. Ing. Petr Dostál, CSc.