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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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Process Control with Dynamic Resource Scheduling
Šinkora, Jan ; Kočí, Radek (referee) ; Janoušek, Vladimír (advisor)
This project pursues issues on the border of information technologies and process optimization. Previously published concepts of~modeling projects and shared resources with object-oriented Petri nets are presented and further expanded. The possibilites of~the use of~genetic algorithms for dynamic realtime optimization of the resource schedules are explored. The resource constrained project sheduling problem is presented and it is shown, how instances of the problem can be implemented. A more complex model that is inspired by real production systems is then created. Next, a control agent, which monitors a running production system and allows for it's dynamic optimization is designed. The whole system is implemented in the Squeak Smalltalk environment with the use of the tool PNtalk, which is an experimental implementation of the object oriented Petri nets paradigm.
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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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Software for Biometric Recognition of a Human Eye Iris
Maruniak, Lukáš ; Orság, Filip (referee) ; Drahanský, Martin (advisor)
In my thesis, I focus on the task of recognizing human iris from an image.In the beginning, the work deals with a question of biometrics, its importance and basic concepts, which are necessary for use in following text. Subsequently process of human Iris detection is described together with theory of evolution algorithms. In the implementation part, is described the design of implemented solution, which uses evolution algorithms, where is emphasis on correct pupil and iris boundary detection.
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Neural networks and evolutionary algorithms
Vágnerová, Jitka ; Rychtárik, Milan (referee) ; Hrubeš, Jan (advisor)
Objective of this master's thesis is optimizing of neral network topology using some of evolutionary algorithms. The backpropagation neural network was optimized using genetic algorithms, evolutionary programming and evolutionary strategies. The text contains an application in the Matlab environment which applies these methods to simple tasks as pattern recognition and function prediction. Created graphs of fitness and error functions are included as a result of this thesis.
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Simulation of Entities Collective Behavior in Virtual World
Vymazal, Tomáš ; Žák, Pavel (referee) ; Láník, Aleš (advisor)
Theme of this work is to evaluate and compare aviable paradigms for entity control in virtual worlds, and to implement one of these paradigms in application. Dynamic finite state machine upgraded using genetic algorithms has been chosen. This paradigm should make agent's behavior better and adapt agent to required state: i.e. make agent harvest resources in virtual world. Output of this work is application for running evolution and application for 3D view of agent's behavior.
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Utilization of inverse reliability analysis tools for probability based design of selected structural parameters
Lipowczan, Martin ; Novák, Drahomír (referee) ; Lehký, David (advisor)
This bachelor thesis deals with the application of methodology and tools of inverse analysis in regards to probabilistic design of selected design parameters of structure. The first step was to get familiar with the probabilistic design and analysis, then understanding of the inverse analysis methodology itself which is based on artificial neural networks. After researching the topic we could get to the actual issue. To put the theory in practice easier examples were used at first. These were mathematical functions and one practical-based example, whereas the results were known in advance. This simplified a process of checking achieved values. Using software tools and especially DLNNET software allowed us to take on practical exercises. Used exercises are chosen from earlier undergraduate studies at the Faculty of Civil Engineering, Brno. The first of these was a design of reinforced concrete slab, where desired parameters were slab’s height and area of reinforcement. The second one was a design of a diagonal truss screw connection, aimed to size the screw diameter and its quantity.
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Planar Antennas on Electromagnetic Bandgap Substrates
Horák, Jiří ; Dědková, Jarmila (referee) ; Škvor,, Zbyněk (referee) ; Raida, Zbyněk (advisor)
Planar antennas are used in several technical applications. The family of planar antennas contains microstrip antennas, which are very popular due to the low weight, low profile, simple manufacturing and easy mass production. Lower gain and excitation of surface waves are disadvantages of microstrip antennas. The propagation of surface waves can be efficiently suppressed if the conventional substrate is replaced by an electromagnetic bandgap (EBG) substrate. Microstrip antennas on EBG substrates have been presented in an open literature for several years. Nevertheless, no published work is devoted to the design of EBG substrates, which can suppress surface waves at several frequencies those cannot be covered by a single bandgap. In order to reach optimum parameters of designed antennas, selected global optimization methods are applied (genetic algorithms, particle swarm optimization, ant colony optimization).
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Travelling Salesman Problem
Kolář, Adam ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
The aim of this bachelor's thesis is to design a testing environment for the traveling salesman problem and compare the effectiveness of different approaches to the solution. The first part discussed the possibility of genetic algorithms, depending on the setting of a crossover, mutations and population size. In the second part, there is the same problem using two types of neural networks. The representative of the self-learning net was chosen Kohonen neural network. Hopfield neural network represents a method of minimizing the energy function with fixed coefficients. At both neural networks, there were described possible advantages and disadvantages. In the end, all the findings were interpreted in a global context.
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