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Optimisation of TSP-Based Tasks Using Collective Computational Intelligence
Franěk, Jaromír ; Jaroš, Jiří (referee) ; Bidlo, Michal (advisor)
The aim of this work is to compare collective computational intelligence algorithms for the optimization of large-scale instances of traveling salesman problem consisting of in several of thousands of cities. This work will be focused on optimization based on swarm behavior and optimization based on bee swarm behavior. I have compared individual algorithms from these two approaches with different parameters within a set of experiments. Based on these results, I proposed an improvement to the algorithms for solving the given problem. Then I proposed an improvement to the algorithms using diversity support methods, or local search for discrete versions of these algorithms. Finally, I compared results of proposed algorithms within a final set of experiments.
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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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Unmanned aerial vehicle path planning by evolutionary algorithms
Miloševič, Filip ; Šoustek, Petr (referee) ; Kůdela, Jakub (advisor)
This bachelor thesis deals with the problem of optimizing UAV routes in 3D space. It consists of a review of the current knowledge regarding the issue and the implementation of a program with a graphical interface that can create an optimized route using the Artificial Bee Colony, Particle Swarm Optimization and Whale Optimization Algorithms. Subsequently, a series of simulations were performed using the program, in which the Artificial Bee Colony algorithm proved to be the most effective algorithm in solving this issue.
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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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