|
|
Neural networks and evolutionary algorithms
Vágnerová, Jitka ; Rychtárik, Milan (referee) ; Hrubeš, Jan (advisor)
Objective of this master's thesis is optimizing of neral network topology using some of evolutionary algorithms. The backpropagation neural network was optimized using genetic algorithms, evolutionary programming and evolutionary strategies. The text contains an application in the Matlab environment which applies these methods to simple tasks as pattern recognition and function prediction. Created graphs of fitness and error functions are included as a result of this thesis.
|
|
|
Image filters for evolutionary programming
Zavadil, Miloš ; Beneš, Radek (referee) ; Burget, Radim (advisor)
Image filters is a subset of signal processing. Image filtering is mainly used for highlighting an information. It can be useful for reduce noise, smooth pictures, enhance contrast or for edge detection. Image filter design itself is a time-consuming process. It is suitable to automate the process and give up the function of filter designing to preprogrammed system. Designing komponents for that system is aim of this work. It is part of an whole expert system. A set of information is given on input which are used for generating new image filters. Subsequently it will evaluate the relevancy of concrete image filter for subsequent use.
|
|
|
Utilization of Evolutionary Algorithms in Symbolic Regression Problem
Komadel, Michal ; Slaný, Karel (referee) ; Vašíček, Zdeněk (advisor)
Evolutionary algorithms are constantly developing and progressive part of informatics. These algorithms serve to solve many kinds of problems from optimal control to planning. This study discusses genetic and cartesian genetic programming, which belong among the most successful types of evolutionary algorithms. The goal of this work is to develop two aplications of genetic and cartesian genetic programming and evaluate efficiency of these two types of evolutionary algorithms in solving symbolic regression problems.
|
|
|
Evolutionary Prediction of Time Series
Křivánek, Jan ; Bidlo, Michal (referee) ; Sekanina, Lukáš (advisor)
This thesis summarizes knowledge in the field of time series theory, method for time series analysis and applications in financial modeling. It also resumes the area of evolutionary algorithms, their classification and applications. The core of this work combines these knowledges in order to build a system utilizing evolutionary algorithms for financial time series forecasting models optimization. Various software engineering techniques were used during the implementation phase (ACI - autonomous continual integration, autonomous quality control etc.) to ensure easy maintainability and extendibility of project by more developers.
|
|
|
Evolutionary Prediction of Time Series
Křivánek, Jan ; Bidlo, Michal (referee) ; Sekanina, Lukáš (advisor)
This thesis summarizes knowledge in the field of time series theory, method for time series analysis and applications in financial modeling. It also resumes the area of evolutionary algorithms, their classification and applications. The core of this work combines these knowledges in order to build a system utilizing evolutionary algorithms for financial time series forecasting models optimization. Various software engineering techniques were used during the implementation phase (ACI - autonomous continual integration, autonomous quality control etc.) to ensure easy maintainability and extendibility of project by more developers.
|
|
|
Utilization of Evolutionary Algorithms in Symbolic Regression Problem
Komadel, Michal ; Slaný, Karel (referee) ; Vašíček, Zdeněk (advisor)
Evolutionary algorithms are constantly developing and progressive part of informatics. These algorithms serve to solve many kinds of problems from optimal control to planning. This study discusses genetic and cartesian genetic programming, which belong among the most successful types of evolutionary algorithms. The goal of this work is to develop two aplications of genetic and cartesian genetic programming and evaluate efficiency of these two types of evolutionary algorithms in solving symbolic regression problems.
|
|
|
Image filters for evolutionary programming
Zavadil, Miloš ; Beneš, Radek (referee) ; Burget, Radim (advisor)
Image filters is a subset of signal processing. Image filtering is mainly used for highlighting an information. It can be useful for reduce noise, smooth pictures, enhance contrast or for edge detection. Image filter design itself is a time-consuming process. It is suitable to automate the process and give up the function of filter designing to preprogrammed system. Designing komponents for that system is aim of this work. It is part of an whole expert system. A set of information is given on input which are used for generating new image filters. Subsequently it will evaluate the relevancy of concrete image filter for subsequent use.
|
|
|
Neural networks and evolutionary algorithms
Vágnerová, Jitka ; Rychtárik, Milan (referee) ; Hrubeš, Jan (advisor)
Objective of this master's thesis is optimizing of neral network topology using some of evolutionary algorithms. The backpropagation neural network was optimized using genetic algorithms, evolutionary programming and evolutionary strategies. The text contains an application in the Matlab environment which applies these methods to simple tasks as pattern recognition and function prediction. Created graphs of fitness and error functions are included as a result of this thesis.
|
|
| |
guest ::
