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Image registration of ultrasound sequences using evolutionary algorithms
Hnízdilová, Bohdana ; Odstrčilík, Jan (referee) ; Mézl, Martin (advisor)
This master´s thesis deals with the registration of ultrasound sequences using evolutionary algorithms. The theoretical part of the thesis describes the process of image registration and its optimalization using genetic and metaheuristic algorithms. The thesis also presents problems that may occur during the registration of ultrasonographic images and various approaches to their registration. In the practical part of the work, several optimization methods for the registration of a number of sequences were implemented and compared.
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Test Optimization by Search-Based Algorithms
Starigazda, Michal ; Holík, Lukáš (referee) ; Letko, Zdeněk (advisor)
Testing of multi-threaded programs is a demanding work due to the many possible thread interleavings one should examine. The noise injection technique helps to increase the number of tested thread interleavings by noise injection to suitable program locations. This work optimizes meta-heuristics search techniques in the testing of concurrent programs by utilizing deterministic heuristic in the application of genetic algorithms in a space of legal program locations suitable for the noise injection. In this work, several novel deterministic noise injection heuristics without dependency on the random number generator are proposed in contrary to the most of currently used heuristic. The elimination of the randomness should make the search process more informed and provide better, more optimal, solutions thanks to increased stability in the results provided by novel heuristics. Finally, a benchmark of programs, used for the evaluation of novel noise injection heuristics is presented.
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Solution of Continuous Systems by Evolutionary Computational Techniques
Lang, Stanislav ; Šeda, Miloš (referee) ; Olehla, Miroslav (referee) ; Matoušek, Radomil (advisor)
The thesis deals the issue of solution of continuous systems by evolutionary computational techniques. Evolutionary computing techniques fall into the field of softcomputing, an advanced metaheuristics optimization that is becoming more and more a method of solving complicated optimization problems with the gradual increase in computing performance of computers. The solution of continuous systems, or the synthesis of continuous control circuits, is one of the areas where these advanced algorithms find their application. When dealing with continuous systems we will focus on regulatory issues. Evolutionary computing can then become a tool not only for optimization of controller parameters but also to design its structure. Various algorithms (genetic algorithm, differential evolution, etc.) can be used to optimize the parameters of the controller, for the design of the controller structurewe usually encounter so called grammatical evolution. However, the use of grammatical evolution is not necessary if appropriate coding is used, as suggested in the presented thesis. The thesis presents a method of designing the structure and parameters of a general linear controller using the genetic algorithm. A general linear regulator is known also as so called polynomial controller, if we encounter the polynomial theory of control. The method of encoding the description of the general linear controller into the genetic chain is crucial, it determines a set of algorithms that are usable for optimization and influence the efficiency of the calculations. Described coding, effective EVT implementation, including multi-criteria optimization, is a key benefit of this work.
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Analysis and Testing of Concurrent Programs
Letko, Zdeněk ; Lourenco, Joao (referee) ; Sekanina, Lukáš (referee) ; Vojnar, Tomáš (advisor)
V disertační práci je nejprve uvedena taxonomie chyb v souběžném zpracování dat a přehled technik pro jejich dynamickou detekci. Následně jsou navrženy nové metriky pro měření synchronizace a souběžného chování programů společně s metodologií jejich odvozování. Tyto techniky se zejména uplatní v testování využívajícím techniky prohledávání prostoru a v saturačním testování. Práce dále představuje novou heuristiku vkládání šumu, jejímž cílem je maximalizace proložení instrukcí pozorovaných během testování. Tato heuristika je porovnána s již existujícími heuristikami na několika testech. Výsledky ukazují, že nová heuristika překonává ty existující v určitých případech. Nakonec práce představuje inovativní aplikaci stochastických optimalizačních algoritmů v procesu testování vícevláknových aplikací. Principem metody je hledání vhodných kombinací parametrů testů a metod vkládání šumu. Tato metoda byla prototypově implementována a otestována na množině testovacích příkladů. Výsledky ukazují, že metoda má potenciál vyznamně vylepšit testování vícevláknových programů.
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Optimization by means of metaheuristics in Python using the DEAP library
Kesler, René ; Charvát, Pavel (referee) ; Klimeš, Lubomír (advisor)
{This thesis deals with optimization by means of metaheuristics, which are used for complicated engineering problems that cannot be solved by classical methods of mathematical programming. At the beginning, choosed metaheuristics are described: simulated annealing, particle swarm optimization and genetic algorithm; and then they are compared with use of test functions. These algorithms are implemented in Python programming language with use of package called DEAP, which is also described in this thesis. Algorithms are then applied for optimization of design parameters of the heat storage unit.
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Aerofoil Aerodynamic Features Optimization
Müller, Jan ; Rozehnal,, Dalibor (referee) ; Popela, Robert (referee) ; Zelinka, Ivan (referee) ; Ošmera, Pavel (advisor)
The content of the presented thesis is advanced optimization of the aerofoil wing of a general aircraft. Advanced metaheuristic optimization techniques based on evolutionary calculations and swarm algorithms are used for optimization. These algorithms are characterized by robustness of optimization and engineered degree of convergence and optimality of the solution. Within the solution, fundamental modifications of the original aerofoil optimizations were designed and implemented. A new variant of aerofoil evolutionary algorithms (aEA) was created from the original evolutionary algorithm (EA), followed by a new variant of aerofoil particle swarm optimization (aPSO) developed from the original particle swarm optimization (PSO). Then the hybridization of the mentioned methods was created in a parallel variant. The Bezier-PARSEC 3434 parameterization model that generates the aerofoil shape was used for the optimization process. A parametric model based on B-Spline was used to optimize the original aerofoil. Fluid dynamics simulation for the calculation of basic aerodynamic features (lift, drag, moment) was realized by Xfoil software. The results are then verified using fluid dynamics simulation (CFD ANSYS Fluent). From the point of view of optimization tasks developed by optimization and implementation, it is clear that this is a complex interdisciplinary task, the results of which are presented in this thesis.
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Aerofoil Aerodynamic Features Optimization
Müller, Jan ; Popela, Robert (referee) ; Zelinka, Ivan (referee) ; Rozehnal,, Dalibor (referee) ; Ošmera, Pavel (advisor)
The content of the presented thesis is advanced optimization of the aerofoil wing of a general aircraft. Advanced metaheuristic optimization techniques based on evolutionary calculations and swarm algorithms are used for optimization. These algorithms are characterized by robustness of optimization and engineered degree of convergence and optimality of the solution. Within the solution, fundamental modifications of the original aerofoil optimizations were designed and implemented. A new variant of aerofoil evolutionary algorithms (aEA) was created from the original evolutionary algorithm (EA), followed by a new variant of aerofoil particle swarm optimization (aPSO) developed from the original particle swarm optimization (PSO). Then the hybridization of the mentioned methods was created in a parallel variant. The Bezier-PARSEC 3434 parameterization model that generates the aerofoil shape was used for the optimization process. A parametric model based on B-Spline was used to optimize the original aerofoil. Fluid dynamics simulation for the calculation of basic aerodynamic features (lift, drag, moment) was realized by Xfoil software. The results are then verified using fluid dynamics simulation (CFD ANSYS Fluent). From the point of view of optimization tasks developed by optimization and implementation, it is clear that this is a complex interdisciplinary task, the results of which are presented in this thesis.
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Image registration of ultrasound sequences using evolutionary algorithms
Hnízdilová, Bohdana ; Odstrčilík, Jan (referee) ; Mézl, Martin (advisor)
This master´s thesis deals with the registration of ultrasound sequences using evolutionary algorithms. The theoretical part of the thesis describes the process of image registration and its optimalization using genetic and metaheuristic algorithms. The thesis also presents problems that may occur during the registration of ultrasonographic images and various approaches to their registration. In the practical part of the work, several optimization methods for the registration of a number of sequences were implemented and compared.
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Optimization by means of metaheuristics in Python using the DEAP library
Kesler, René ; Charvát, Pavel (referee) ; Klimeš, Lubomír (advisor)
{This thesis deals with optimization by means of metaheuristics, which are used for complicated engineering problems that cannot be solved by classical methods of mathematical programming. At the beginning, choosed metaheuristics are described: simulated annealing, particle swarm optimization and genetic algorithm; and then they are compared with use of test functions. These algorithms are implemented in Python programming language with use of package called DEAP, which is also described in this thesis. Algorithms are then applied for optimization of design parameters of the heat storage unit.
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Solution of Continuous Systems by Evolutionary Computational Techniques
Lang, Stanislav ; Šeda, Miloš (referee) ; Olehla, Miroslav (referee) ; Matoušek, Radomil (advisor)
The thesis deals the issue of solution of continuous systems by evolutionary computational techniques. Evolutionary computing techniques fall into the field of softcomputing, an advanced metaheuristics optimization that is becoming more and more a method of solving complicated optimization problems with the gradual increase in computing performance of computers. The solution of continuous systems, or the synthesis of continuous control circuits, is one of the areas where these advanced algorithms find their application. When dealing with continuous systems we will focus on regulatory issues. Evolutionary computing can then become a tool not only for optimization of controller parameters but also to design its structure. Various algorithms (genetic algorithm, differential evolution, etc.) can be used to optimize the parameters of the controller, for the design of the controller structurewe usually encounter so called grammatical evolution. However, the use of grammatical evolution is not necessary if appropriate coding is used, as suggested in the presented thesis. The thesis presents a method of designing the structure and parameters of a general linear controller using the genetic algorithm. A general linear regulator is known also as so called polynomial controller, if we encounter the polynomial theory of control. The method of encoding the description of the general linear controller into the genetic chain is crucial, it determines a set of algorithms that are usable for optimization and influence the efficiency of the calculations. Described coding, effective EVT implementation, including multi-criteria optimization, is a key benefit of this work.
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