National Repository of Grey Literature 51 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
GUI for Handling Genetic Programming Chromozome
Staurovská, Jana ; Žaloudek, Luděk (referee) ; Jaroš, Jiří (advisor)
The main goal of this thesis is to create a program for manipulation with genetic programming chromosomes, which should allow export to a vector graphics format, moving of gates, their colouring and other graphical operations, and will work on different operating systems (mainly Microsoft Windows and Linux). For better understanding, the basic principles of cartesian genetic programming are described in theoretical part.
Implementation and Visualization of Classic Genetic Algorithm Using Metropolis Algorithm
Matula, Radek ; Jaroš, Jiří (referee) ; Ohlídal, Miloš (advisor)
This bachelor's thesis contains description of utilisation genetic and Metropolis algorithm to solution the Traveling Salesman Problem (TSP). Thesis describes process of development aplication POC and explains problems with adjusting parameters of algorithm.
Evolutionary algorithms
Bortel, Martin ; Karásek, Jan (referee) ; Burget, Radim (advisor)
Thesis describes main attributes and principles of Evolutionary and Genetic algorithms. Crossover, mutation and selection are described as well as termination options. There are examples of practical use of evolutionary and genetic algorithms. Optimization of distribution routes using PHP&MySQL and Google Maps API technologies.
Genetic Algorithm Design for Distribution Network Outfits Optimalization
Ondruš, Tomáš ; Skala, Petr (referee) ; Paar, Martin (advisor)
The work deals with genetic algorithms and their potential use in application software to optimize high voltage switching elements of distribution network. Theoretical part explains the basic concepts of genetic algorithms such as a gene, population and chromosome and basic principles of the development of genetic algorithms.. The main task of the thesis is to design the algorithm that will simulate the distribution of the sectionalizers by telecontrolled section switches or reclosers and analyze how to set the the parameters affecting the convergence speed of genetic algorithm. The basic parameters affecting the convergence of breeding, mutation probability, population size or using of elitism. The second goal is finding a suitable set of input parameters for the selected population sizes without and with using elitism. The results of the work determine the most appropriate settings for each generation and determining the approximate number of generations needed to find the best solution. The genetic algorithm applocation was tested on a less extensive distribution network with six switching elements
Evolutionary algorithms
Bortel, Martin ; Karásek, Jan (referee) ; Lambertová, Petra (advisor)
Thesis describes main attributes and principles of Evolutionary and Genetic algorithms. Crossover, mutation and selection are described as well as termination options. There are examples of practical use of evolutionary and genetic algorithms. Optimization of distribution routes using PHP&MySQL and Google Maps API technologies.
A Tool for Visual Analysis of Circuit Evolution
Staurovská, Jana ; Minařík, Miloš (referee) ; Sekanina, Lukáš (advisor)
The main goal of the master's thesis is to compose a study on cartesian genetic programming with focus on evolution of circuits and to design a concept for visualisation of this evolution. Another goal is to create a program to visualise the circuit evolution in cartesian genetic programming, its generations and chromosomes. The program is capable of visualising the changes between generations and chromosomes and comparing more chromosomes at once. Several user cases had been prepared for the resulting program.
Genetic Algorithms
Masárová, Mária ; Zbořil, František (referee) ; Zbořil, František (advisor)
This thesis deals with genetic algorithm, their terminology and use. It describes various problems that can be solved by using genetic algorithms. Different algorithms of swarm intelligence are also presented in this thesis, while firefly algorithm also serves to compare the efficiency between it and genetic algorithm. The main task of this thesis is to perform experiments with three optimization tasks, namely, travelling salesman problem, boolean satisfiability problem and searching for extreme in function.
Discovery of Wireless Sensor Network Topology Using Genetic Algorithms
Dalecký, Štěpán ; Samek, Jan (referee) ; Zbořil, František (advisor)
The thesis deals with a design of the genetic algorithm that is able to discover the wireless sensor network topology using signal strength among particular sensors. At first, the thesis describes the theory of genetic algorithm and wireless sensor network. Subsequently, on the basis of this theory, the genetic algorithm serving for the wireless sensor network topology discovery has been designed. The thesis also describes important features of the algorithm implementation. In conclusion, the outcomes have been reviewed.
Digital image analysis of mitotic chromosomes
Jaroš, Luboš ; Vítek, Martin (referee) ; Škutková, Helena (advisor)
The development in modern medicine has allowed to study human genome and detect predispositions to several diseases. One of very promising techniques is the analysis of human karyotype, i.e., the number and appearance of chromosomes in the cell nucleus. The most important step in the karyotype analysis is the chromosome detection and categorization. In this work, a new algorithm for detection of chromosomes from an image of microscopic DNA sample and their categorization into seven groups was developed. The algorithm was implemented in Matlab. The accuracy of segmentation and classification was tested on a set of images from two databases with 117 and 38 images, respectively. The sensitivity of the developed segmentation reached 88% while the value of positive predictivity of segmentation reached 92%. The success rate of chromosome pairing achieves 77%.
Optimization of Processes in Logistics with Visualization Support
Kršák, Martin ; Bidlo, Michal (referee) ; Křivka, Zbyněk (advisor)
The master thesis aims to design, implement, and compare algorithms that optimize processes in logistics, mainly in the planning phase. Heuristics and approximation genetic algorithms will find an near-optimal solution to NP-hard problem, such as the traveling salesman problem, with a delay less than several hours. The role of this algorithm is to plan an efficient route for garbage trucks that collect and distribute large-scale waste to waste yards in a specific city. The goal of the optimization is to minimize the shipping costs.

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