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Generating 3D Trees Based on Real Images
Kubiš, František ; Polok, Lukáš (referee) ; Szentandrási, István (advisor)
Master's thesis studies the possibilities of generating 3D trees using variety of methods including context-free grammars and L-systems. Master's thesis also includes chapter on evolutionary and genetic algorithms, which briefly summarize their function. In this project genetic algorithm which takes 2D image of tree and the beginning of its trunk is proposed. Based on this information it will generate 3D tree which is visually close to the original image. In addition to methods of generating trees, reader will get information about processing input image and designing test application.
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Evolutionary Algorithms in the Task of Boolean Satisfiability
Serédi, Silvester ; Vašíček, Zdeněk (referee) ; Sekanina, Lukáš (advisor)
The goal of this Master's Thesis is finding a SAT solving heuristic by the application of an evolutionary algorithm. This thesis surveys various approaches used in SAT solving and some variants of evolutionary algorithms that are relevant to this topic. Afterwards the implementation of a linear genetic programming system that searches for a suitable heuristic for SAT problem instances is described, together with the implementation of a custom SAT solver which expoloits the output of the genetic program. Finally, the achieved results are summarized.
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Application of Evolutionary Algorithm in Creation of Regression Tests
Belešová, Michaela ; Kajan, Michal (referee) ; Zachariášová, Marcela (advisor)
This master thesis deals with application of an evolutionary algorithm in the creation of regression tests. In the first section, description of functional verification, verification methodology, regression tests and evolutionary algorithms is provided. In the following section, the evolutionary algorithm, the purpose of which is to achieve reduction of the number of test vectors obtained in the process of functional verification, is proposed. Afterwards, the proposed algorithm is implemented and a set of experiments is evaluated. The results are discussed.
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Fast Detection of Application Protocols
Grochol, David ; Vašíček, Zdeněk (referee) ; Sekanina, Lukáš (advisor)
Master thesis is focused on classification of application protocols based on application data taken from layer L7 of ISO/OSI model. The aim of the thesis is to suggest a classifier for SDM system (Software defined monitoring) so it could be used for links with throughput up to 100 Gb/s. At the same time it should classify with the fewest possible errors.Designed classifier consists of two parts. First part depicts encoders for encoding selected attributes. Second part deals with evaluating circuit which detects series characteristic for particular application protocols on the output from the first part. Considered attributes and series are taken from statistic analyzes of application protocol data.The classifier itself is designed so it can be implemented in FPGA and enables modification set of application protocols who intended for classification. The quality of designed classifier is tested on real network data. The results of classification are compared with current methods used for classification of application protocols.
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Acceleration of Transistor-Level Evolutionary Design of Digital Circuits Using Zynq
Mrázek, Vojtěch ; Sekanina, Lukáš (referee) ; Vašíček, Zdeněk (advisor)
The goal of this project is to design a hardware unit that is designed to accelerate evolutionary design of digital circuits on transistor level. The project is divided to two parts. The first one describes design methods of the MOSFET circuits and issues of evolutionary algorithms. It also analyses current results in this domain and provides a new method for the design and optimization. The second part describes proposed unit that accelerates the new method on the circuit Zynq which integrates ARM processor and programmable logic. The new method functionality has been empirically analysed in the task of optimization of few circuits with more inputs. The hardware unit has been tested for designing of gates on transistor level.
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Coevolutionary Algorithm for Test-Based Problems
Hulva, Jiří ; Sekanina, Lukáš (referee) ; Drahošová, Michaela (advisor)
This thesis deals with the usage of coevolution in the task of symbolic regression. Symbolic regression is used for obtaining mathematical formula which approximates the measured data. It can be executed by genetic programming - a method from the category of evolutionary algorithms that is inspired by natural evolutionary processes. Coevolution works with multiple evolutionary processes that are running simultaneously and influencing each other. This work deals with the design and implementation of the application which performs symbolic regression using coevolution on test-based problems. The test set was generated by a new method, which allows to adjust its size dynamically. Functionality of the application was verified on a set of five test tasks. The results were compared with a coevolution algorithm with a fixed-sized test set. In three cases the new method needed lesser number of generations to find a solution of a desired quality, however, in most cases more data-point evaluations were required.
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A Tool for Analysis of Digital Circuit Evolution Records
Kapusta, Vlastimil ; Bidlo, Michal (referee) ; Sekanina, Lukáš (advisor)
This master thesis describes stochastic optimization algorithms inspired in nature that use population of individuals - evolutionary algorithms. Genetic programming and its variant - cartesian genetic programming is described in a greater detail. This thesis is further focused on the analysis and visualization of digital circuit evolution records. Existing tools for visualization of the circuit evolution were analysed, but because no suitable tool allowing complex analysis of the circuit evolution was found, a new set of functions was proposed and the principles of a new tool were formulated. These functions were implemented in form of an interactive GUI application in Java programming language. The application was described in detail and then used for analysis of digital circuit evolution records.
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Coevolution of Image Filters and Fitness Predictors
Trefilík, Jakub ; Hrbáček, Radek (referee) ; Drahošová, Michaela (advisor)
This thesis deals with employing coevolutionary principles to the image filter design. Evolutionary algorithms are very advisable method for image filter design. Using coevolution, we can add the processes, which can accelerate the convergence by interactions of candidate filters population with population of fitness predictors. Fitness predictor is a small subset of the training set and it is used to approximate the fitness of the candidate solutions. In this thesis, indirect encoding is used for predictors evolution. This encoding represents a mathematical expression, which selects training vectors for candidate filters fitness prediction. This approach was experimentally evaluated in the task of image filters for various intensity of random impulse and salt and pepper noise design and the design of the edge detectors. It was shown, that this approach leads to adapting the number of target objective vectors for a particular task, which leads to computational complexity reduction.
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Optimization of Aircraft Tracker Parameters
Samek, Michal ; Vlk, Jan (referee) ; Smrž, Pavel (advisor)
Diplomová práce se zabývá optimalizací systému pro sledování letadel, využívaného pro řízení letového provozu. Je popsána metodika vyhodnocování přesnosti sledovacího systému a přehled relevantních algoritmů pro sledování objektů. Dále jsou navrženy tři přístupy k řešení problému. První se pokouší identifikovat parametry filtrovacích algoritmů pomocí algoritmu Expectation-Maximisation, implementací metody maximální věrohodnosti. Druhý přístup je založen na prostých odhadech parametrů normálního rozložení z naměřených a referenčních dat. Nakonec je zkoumána možnost řešení pomocí optimalizačního algoritmu Evoluční strategie. Závěrečné vyhodnocení ukazuje, že třetí přístup je pro daný problém nejvhodnější.
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