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Aplikace evolučního algoritmu na optimalizační úlohu vibračního generátoru
Nguyen, Manh Thanh ; Kovář, Jiří (referee) ; Hadaš, Zdeněk (advisor)
This thesis will deal with the use of artificial intelligence methods for solving optimization problems with multiple variables. A theorethical part presents problems of global optimization and overview of solution methods. For practical reasons, special attention is paid to evolutionary algorithms. The subject of optimization itself is energy harvester based on a piezoelectric effect. Its nature and modeling is devoted to one chapter. A part of the thesis is the implementation of the SOMA algorithm for finding the optimal parameters of the generator for maximum performance.
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The global optimalization methods
Dudová, Aneta ; Kozumplík, Jiří (referee) ; Mézl, Martin (advisor)
This bachelor work is dedicated to advanced methods of global optimization, and especially problem traveling salesman. It focuses on the description of the problem and its various options, including graph theory, heuristic algorithms, evolutionary algorithms, in which mainly genetic algorithms and optimization by ant colonies. In conclusion, the implementation of these methods and performed testing on different data sets of algorithms that approximately solve the traveling salesman problem.
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Synthesis of electromagnetic bandgap structures
Šedý, Michal ; Kovács, Peter (referee) ; Raida, Zbyněk (advisor)
In microwave frequency band, the planar technology is mainly used to fabricate electronic circuits. Propagation of surface waves belongs to the significant problem of this technology. Surface waves can cause unwanted coupling among particular parts of the structure and can degrade its parameters. The problem can be solved using an electromagnetic band gap structure (EBG). These periodic structures are able to suppress surface waves in different frequency bands. This thesis is focused on the modeling of these structures in the program COMSOL Multiphysics.
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Reconstruction of the Antenna Near-Field
Puskely, Jan ; Mazánek, Miloš (referee) ; Schejbal, Vladimír (referee) ; Nováček, Zdeněk (advisor)
Cílem disertační práce je navrhnout efektivně pracující algoritmus, který na základě bezfázového měření v blízkém poli antény bude schopen zrekonstruovat komplexní blízké pole antény resp. vyzařovací diagram antény ve vzdáleném poli. Na základě těchto úvah byly zkoumány vlastnosti minimalizačního algoritmu. Zejména byl analyzován a vhodně zvolen minimalizační přistup, optimalizační metoda a v neposlední řadě i optimalizační funkce tzv. funkcionál. Dále pro urychlení celého minimalizačního procesu byly uvažovány prvotní odhady. A na závěr byla do minimalizačního algoritmu zahrnuta myšlenka nahrazující hledané elektrické pole několika koeficienty. Na základě předchozích analýz byla navržená bezfázová metoda pro charakterizaci vyzařovacích vlastností antén. Tato metoda kombinuje globální optimalizaci s obrazovou kompresní metodou a s lokální metodou ve spojení s konvečním amplitudovým měřením na dvou površích. V našem případě je globální optimalizace použita k nalezení globálního minima minimalizovaného funkcionálu, kompresní metoda k redukci neznámých proměnných na apertuře antény a lokální metoda zajišťuje přesnější nalezení minima. Navržená metoda je velmi robustní a mnohem rychlejší než jiné dostupné minimalizační algoritmy. Další výzkum byl zaměřen na možnosti využití měřených amplitud pouze z jednoho měřícího povrchu pro rekonstrukci vyzařovacích charakteristik antén a využití nového algoritmu pro rekonstrukci fáze na válcové geometrii.
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Theoretical insights into encapsulated noble metals
Hou, Dianwei ; Heard, Christopher James (advisor) ; Logsdail, Andrew (referee) ; Rubeš, Miroslav (referee)
Noble metals are widely used in industry due to their excellent catalytic and optical properties. Because of limited reserves and high prices, it is desired to make effective use of every atom. It has been possible in recent years to produce subnanometer clusters or even isolated atoms, despite their low resistance against sintering. Furthermore, it has been recently established that the encapsulation of single atoms and subnanometer noble metal clusters can be achieved via trapping at metal oxides, ranging from two-dimensional layered materials to the void space within the pores of zeolites. However, neither the atomistic mechanisms of atom/cluster trapping, nor the means by which they may be optimized are known. Furthermore, the relationship between the physical and electronic state of trapped atoms/clusters and their reactive properties in catalysis are currently only weakly understood. In this thesis, we used theoretical methods ranging from global structure optimization to kinetic Monte Carlo to identify the roles of cluster size, charge state, and the present and type of common adsorbents on the stability, catalytic and optical properties of subnanometre-sized noble metal clusters trapped at metal oxides. This thesis takes the form of three sections: (1) Structure, stability, and migration...
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Bayesian Optimization of Hyperparameters Using Gaussian Processes
Arnold, Jakub ; Straka, Milan (advisor) ; Vomlelová, Marta (referee)
The goal of this thesis was to implement a practical tool for optimizing hy- perparameters of neural networks using Bayesian optimization. We show the theoretical foundations of Bayesian optimization, including the necessary math- ematical background for Gaussian Process regression, and some extensions to Bayesian optimization. In order to evaluate the performance of Bayesian op- timization, we performed multiple real-world experiments with different neural network architectures. In our comparison to a random search, Bayesian opti- mization usually obtained a higher objective function value, and achieved lower variance in repeated experiments. Furthermore, in three out of four experi- ments, the hyperparameters discovered by Bayesian optimization outperformed the manually designed ones. We also show how the underlying Gaussian Process regression can be a useful tool for visualizing the effects of each hyperparameter, as well as possible relationships between multiple hyperparameters. 1
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Aplikace evolučního algoritmu na optimalizační úlohu vibračního generátoru
Nguyen, Manh Thanh ; Kovář, Jiří (referee) ; Hadaš, Zdeněk (advisor)
This thesis will deal with the use of artificial intelligence methods for solving optimization problems with multiple variables. A theorethical part presents problems of global optimization and overview of solution methods. For practical reasons, special attention is paid to evolutionary algorithms. The subject of optimization itself is energy harvester based on a piezoelectric effect. Its nature and modeling is devoted to one chapter. A part of the thesis is the implementation of the SOMA algorithm for finding the optimal parameters of the generator for maximum performance.
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The global optimalization methods
Dudová, Aneta ; Kozumplík, Jiří (referee) ; Mézl, Martin (advisor)
This bachelor work is dedicated to advanced methods of global optimization, and especially problem traveling salesman. It focuses on the description of the problem and its various options, including graph theory, heuristic algorithms, evolutionary algorithms, in which mainly genetic algorithms and optimization by ant colonies. In conclusion, the implementation of these methods and performed testing on different data sets of algorithms that approximately solve the traveling salesman problem.
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