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The Use of Artificial Intelligence for Decision Making
Nezbedová, Katarína ; Pekárek, Jan (referee) ; Dostál, Petr (advisor)
This bachelor thesis deals with the Tamari attractor problem and its application for forming a prediction model. The core of the work is to create a simulation program in the MATLAB development environment and to use it to create and compare several case studies of a predictive model based on different parameters. This model is graphically illustrated and supplemented by economic interpretation.
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Analýza Duffingova oscilátoru
Sosna, Petr ; Hadraba, Petr (referee) ; Rubeš, Ondřej (advisor)
This thesis analyses the simplest model of nonlinear oscillations, the Duffing oscillator. Methods of nonlinear dynamics are used for analysis of the Duffing equation which describes such oscillations. Numerical solution focuses on the dynamics of twin-well potencial oscillations. The effect of all the parameters of the Duffing equation on the system is shown. Coexisting periodic and chaotic attractors are discussed as well as possible bifurcations of the system. A bifurcation diagram for a specific system is created. The thesis concludes with simulation of basins of attraction for different values of excitation force and frequency.
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Analysis and Prediction of Foreign Exchange Markets by Chaotic Attractors and Neural Networks
Pekárek, Jan ; Dostál, Petr (referee) ; Budík, Jan (advisor)
This thesis deals with a complex analysis and prediction of foreign exchange markets. It uses advanced artificial intelligence methods, namely neural networks and chaos theory. It introduces unconventional approaches and methods of each of these areas, compares them and uses on a real problem. The core of this thesis is a comparison of several prediction models based on completely different principles and underlying theories. The outcome is then a selection of the most appropriate prediction model called NAR + H. The model is evaluated according to several criteria, the pros and cons are discussed and approximate expected profitability and risk are calculated. All analytical, prediction and partial algorithms are implemented in Matlab development environment and form a unified library of all used functions and scripts. It also may be considered as a secondary main outcome of the thesis.
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Analýza Duffingova oscilátoru
Sosna, Petr ; Hadraba, Petr (referee) ; Rubeš, Ondřej (advisor)
This thesis analyses the simplest model of nonlinear oscillations, the Duffing oscillator. Methods of nonlinear dynamics are used for analysis of the Duffing equation which describes such oscillations. Numerical solution focuses on the dynamics of twin-well potencial oscillations. The effect of all the parameters of the Duffing equation on the system is shown. Coexisting periodic and chaotic attractors are discussed as well as possible bifurcations of the system. A bifurcation diagram for a specific system is created. The thesis concludes with simulation of basins of attraction for different values of excitation force and frequency.
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The Use of Artificial Intelligence for Decision Making
Nezbedová, Katarína ; Pekárek, Jan (referee) ; Dostál, Petr (advisor)
This bachelor thesis deals with the Tamari attractor problem and its application for forming a prediction model. The core of the work is to create a simulation program in the MATLAB development environment and to use it to create and compare several case studies of a predictive model based on different parameters. This model is graphically illustrated and supplemented by economic interpretation.
|
|
|
Analysis and Prediction of Foreign Exchange Markets by Chaotic Attractors and Neural Networks
Pekárek, Jan ; Dostál, Petr (referee) ; Budík, Jan (advisor)
This thesis deals with a complex analysis and prediction of foreign exchange markets. It uses advanced artificial intelligence methods, namely neural networks and chaos theory. It introduces unconventional approaches and methods of each of these areas, compares them and uses on a real problem. The core of this thesis is a comparison of several prediction models based on completely different principles and underlying theories. The outcome is then a selection of the most appropriate prediction model called NAR + H. The model is evaluated according to several criteria, the pros and cons are discussed and approximate expected profitability and risk are calculated. All analytical, prediction and partial algorithms are implemented in Matlab development environment and form a unified library of all used functions and scripts. It also may be considered as a secondary main outcome of the thesis.
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