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Optimal control of intersection signaling
Tinka, Petr ; Šoustek, Petr (referee) ; Kůdela, Jakub (advisor)
This master´s thesis is about the control of a traffic light. In the first, theoretical part of this work, a description of this problem introduce. The following is an overview of the optimization methods used for this problem. The practical part deals with the modeling of the network of traffic lights in program SUMO and the implementation of selected optimization methods on this. Finally, a comparison of results is made.
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Optimization of Cooling Synchronous Machine
Makki, Zbyněk ; Rafajdus,, Pavol (referee) ; Kačor,, Pavol (referee) ; Janda, Marcel (advisor)
The main goal of doctoral thesis is optimization cooling of the synchronous machine. Problem is solved based on the finite element method with use of ANSYS software. Work is built up from theoretical part where is comparison of base equations for heat transfer and simulations for several models. Next part shows us two methods how simulate free and force convection. Depends on the better method from the previous two methods is used for next calculations with several algorithm which are used for find of best parameters for synchronous machine. Our control parameter is mass flow rate.
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Application of Evolutionary Algorithms in Quantum Computing
Žufan, Petr ; Mrázek, Vojtěch (referee) ; Bidlo, Michal (advisor)
In this thesis, an evolutionary system for searching quantum operators in the form of unitary matrices is implemented. The aim is to propose several representations of candidate solutions and settings of the evolutionary algorithm. Two evolutionary algorithms were applied: the genetic algorithm and evolutionary strategy. Furthermore, a method of generating a unitary matrix is presented which is used for the first time for this task. This method is in some aspects better than the previous ones. Finally, a comparison of all used techniques is shown in experiments.
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Evolutionary Design of Moving Objects
Fajkus, Jakub ; Schwarz, Josef (referee) ; Bidlo, Michal (advisor)
The aim of this work is to implement a system for automatic evolutionary design of virtual robot controllers. In particular, Linear Genetic Programming representation combined with a steady-state genetic algorithm will be used to find a suitable program that will lead a given virtual robot across a sequence of points denoting a predefined trajectory. The MuJoCo physics engine is applied to allow the user to specify the robot shape and to evaluate its behavior according to candidate programs generated by the genetic algorithm. The goal is to train the robot to follow the given path by optimizing the distance of the robot from the given points during the simulation. The optimization is performed by evolving the programs for a given number of generation of the genetic algorithm. Several sets of experiments will be presented and obtained results will be evaluated.
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Evolutionary Design Using Grammatical Evolution
Repík, Tomáš ; Zachariášová, Marcela (referee) ; Bidlo, Michal (advisor)
p, li { white-space: pre-wrap; } Evoluce v přírodě slouží jako zdroj inspirace pro tuto práci . Základní myšlenkou je využití generativní síly gramatik v kombinaci s evolučním přístupem . Nabyté znalosti jsou aplikovány na hledání strategií chování v rozmanitých prostředích . Stromy chování jsou modelem , který bývá běžně použit na řízení rozhodování různých umělých inteligencí . Tato práce se zabývá hledáním stromů chování , které budou řídit jedince řešící nasledující dva problémy : upravenou verzi problému cesty koněm šachovnicí a hraní hry Pirátské kostky . Při hledání strategie hráče kostek , byla použita konkurenční koevoluce . Důvodem je obtížnost návrhu spravedlivé fitness funkce hodnotící výkony hráčů .
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Prediction of Values on a Time Line
Maršová, Eliška ; Bařina, David (referee) ; Zemčík, Pavel (advisor)
This work deals with the prediction of numerical series whose application is suitable for prediction of stock prices. They explain the procedures for analysis and works with price charts. Also explains the methods of machine learning. Knowledge is used to build a program that finds patterns in numerical series for estimation.
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Neural Networks Classifier Design using Genetic Algorithm
Tomášek, Michal ; Vašíček, Zdeněk (referee) ; Mrázek, Vojtěch (advisor)
The aim of this work is the genetic design of neural networks, which are able to classify within various classification tasks. In order to create these neural networks, algorithm called NeuroEvolution of Augmenting Topologies (also known as NEAT) is used. Also the idea of preprocessing, which is included in implemented result, is proposed. The goal of preprocessing is to reduce the computational requirements for processing of benchmark datasets for classification accuracy. The result of this work is a set of experiments conducted over a data set for cancer cells detection and a database of handwritten digits MNIST. Classifiers generated for the cancer cells exhibits over 99 % accuracy and in experiment MNIST reduces computational requirements more than 10 % with bringing negligible error of size 0.17 %.
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MATLAB/ Global Optimization Toolbox: Solving Optimization Problems
Švihálková, Kateřina ; Dvořák, Jiří (referee) ; Lang, Stanislav (referee) ; Matoušek, Radomil (advisor)
The bachelor thesis deals with basic description of global optimization methods which are implemented in MATLAB environment. First part of this thesis describes two MATLAB's toolboxes -- Optimization Toolbox and Global Optimization Toolbox. This study also describes chosen algorithms from those toolboxes (Genetic Algorithms, Simulated Annealing, Pattern Search and Fminsearch) and describes it's implementation. The last part is focused on the solving of optimization problems. Rosenbrock's function, Rastrigin's function, Traveling Salesman Problem and Stepped Cantilever Beam Design Problem are being solved by methods mentioned above. Reached results of every task are compared to each other and evaluated.
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