National Repository of Grey Literature 185 records found  beginprevious31 - 40nextend  jump to record: Search took 0.00 seconds. 
Genetic Relatedness Analysis of Approximate Circuits
Krejčík, Vojtěch ; Mrázek, Vojtěch (referee) ; Sekanina, Lukáš (advisor)
The goal of this thesis is analyzing a large library of approximate circuits (EvoApproxLib) which was created using an evolutionary algorithm and used as a source of genetic data for the purposes of this thesis. More specifically it is a relatedness search in a file containing 24 912 8-bit approximate multipliers which were created by evolution from six different fully functioning parent implementations of multiplication. Gate counts and existence of 16 specific subcircuits were used as relatedness indicators. Various classifiers for assigning multipliers to one of six classes corresponding to parent implementations were trained based on these indicators. A classification success rate of up to 77% was achieved using said indicators. The results of this work show that combinations of specific subcircuits are a strong indicator for identifying which parent circuit the given approximate circuit comes from.
Camera calibration by evolutionary algorithms
Klečka, Jan ; Červinka, Luděk (referee) ; Babinec, Tomáš (advisor)
This paper describes the possibility of using evolutionary algorithms (specifically the differential evolution) to figure out interior and exterior parameters of camera. It is an easy and an effective way to solve this problem. Also describe possibility of using graphics processor unit to parallel computing.
Modularity in the Evolutionary Design
Klemšová, Jarmila ; Bidlo, Michal (referee) ; Vašíček, Zdeněk (advisor)
The diploma thesis deals with the evolutionary algorithms and their application in the area of digital circuit design. In the first part, general principles of evolutionary algorithms are introduced. This part includes also the introduction of genetic algorithms and genetic programming. The next chapter describes the cartesian genetic programming and its modifications like embedded, self-modifying or multi-chromosome cartessian genetic programming. Essential part of this work consists of the design and implementation of a modularization technique for evolution circuit design. The proposed approach is evaluated using a set of standard benchmark circuits.
Acceleration of grammatical evolution calculation using the "Kernel trick" method
Kučerová, Anna ; Hůlka, Tomáš (referee) ; Ošmera, Pavel (advisor)
This thesis describing evolutionary algorithms, specifically grammatical evolution, which is implementing in optimization software PonyGE2. Further describes the principle of the kernel trick.
Evolutionary Algorithms
Szöllösi, Tomáš ; Mézl, Martin (referee) ; Kozumplík, Jiří (advisor)
The task of this thesis was focused on comparison selected evolutionary algorithms for their success and computing needs. The paper discussed the basic principles and concepts of evolutionary algorithms used for optimization problems. Author programmed selected evolutionary algorithms and subsequently tasted on various test functions with exactly the given input conditions. Finally the algorithms were compared and evaluated the results obtained for different settings.
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.
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.
Evolutionary algorithms for image registration of dynamic ultrasound sequences
Votýpka, Tomáš ; Odstrčilík, Jan (referee) ; Mézl, Martin (advisor)
Diploma thesis deals with the registration of of dynamic ultrasound sequences using evolutionary algorithms. This work theoretically describes ultrasound imaging, the process of image registration and optimization using optimization and evolutionary algorithms. The practical part of the work describes the implementation of several optimization methods that were implemented in the MATLAB software environment.
Converged Networks and Traffic Tomography by Using Evolutionary Algorithms
Oujezský, Václav ; Sýkora, Jiří (referee) ; Polívka, Michal (referee) ; Škorpil, Vladislav (advisor)
Nowadays, the traffic tomography represents an integral component in converged networks and systems for detecting their behavioral characteristics. The dissertation deals with research of its implementation with the use of evolutionary algorithms. The research was mainly focused on innovation and solving behavioral detection data flows in networks and network anomalies using tomography and evolutionary algorithms. Within the dissertation has been proposed a new algorithm, emerging from the basics of the statistical method survival analysis, combined with a genetics’ algorithm. The proposed algorithm was tested in a model of a self-created network probe using the Python programming language and Cisco laboratory network devices. Performed tests have shown the basic functionality of the proposed solution.
High-Level Object Oriented Genetic Programming in Logistic Warehouse Optimization
Karásek, Jan ; Rakús,, Martin (referee) ; Cvrk, Lubomír (referee) ; Burget, Radim (advisor)
Disertační práce je zaměřena na optimalizaci průběhu pracovních operací v logistických skladech a distribučních centrech. Hlavním cílem je optimalizovat procesy plánování, rozvrhování a odbavování. Jelikož jde o problém patřící do třídy složitosti NP-težký, je výpočetně velmi náročné nalézt optimální řešení. Motivací pro řešení této práce je vyplnění pomyslné mezery mezi metodami zkoumanými na vědecké a akademické půdě a metodami používanými v produkčních komerčních prostředích. Jádro optimalizačního algoritmu je založeno na základě genetického programování řízeného bezkontextovou gramatikou. Hlavním přínosem této práce je a) navrhnout nový optimalizační algoritmus, který respektuje následující optimalizační podmínky: celkový čas zpracování, využití zdrojů, a zahlcení skladových uliček, které může nastat během zpracování úkolů, b) analyzovat historická data z provozu skladu a vyvinout sadu testovacích příkladů, které mohou sloužit jako referenční výsledky pro další výzkum, a dále c) pokusit se předčit stanovené referenční výsledky dosažené kvalifikovaným a trénovaným operačním manažerem jednoho z největších skladů ve střední Evropě.

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