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Neuroevolution Principles and Applications
Herec, Jan ; Strnadel, Josef (referee) ; Bidlo, Michal (advisor)
The theoretical part of this work deals with evolutionary algorithms (EA), neural networks (NN) and their synthesis in the form of neuroevolution. From a practical point of view, the aim of the work is to show the application of neuroevolution on two different tasks. The first task is the evolutionary design of the convolutional neural network (CNN) architecture that would be able to classify handwritten digits (from the MNIST dataset) with a high accurancy. The second task is the evolutionary optimization of neurocontroller for a simulated Falcon 9 rocket landing. Both tasks are computationally demanding and therefore have been solved on a supercomputer. As a part of the first task, it was possible to design such architectures which, when properly trained, achieve an accuracy of 99.49%. It turned out that it is possible to automate the design of high-quality architectures with the use of neuroevolution. Within the second task, the neuro-controller weights have been optimized so that, for defined initial conditions, the model of the Falcon booster can successfully land. Neuroevolution succeeded in both tasks.
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Optimization of PID controller using evolutionary computing techniques
Kočí, Jakub ; Matoušek, Radomil (referee) ; Lang, Stanislav (advisor)
This bachelor thesis deals with using evolutionary computation for tuning up PID controller. In research part there are summarised information about regulation and another background information about quality of regulation and ITAE criterion. Practical part consist of implementing three evolutionary computation algorithms - differential evolution, evolution strategy and genetic algorithm. These and MATLAB's function ga() are compared on two systems mutually and to Ziegler-Nichols rule. Basic comparsion is followed by statistical evaluation on second system.
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Rainfall runoff process in time of climate change
Benáčková, Kateřina ; Janál,, Petr (referee) ; Marton, Daniel (advisor)
The aim of The Diploma Thesis was to compile a conceptual rainfall-runoff model, that would be eligible to model discharge in conditions of climate changes. After thorough verifications of possible variants, user program Runoff Prophet that is eligible to simulate discharge in closing profile of any river basin was compiled within this paper. Runoff Prophet is deterministic lumped model with monthly computation time step and from the hydrologic phenomena it takes soil moisture, evapotranspiration, groundwater flow and the watercourse flow into account. Its calibration is based on the differential evolution principle with Nash–Sutcliffe model efficiency coefficient as the calibration criterion. Developed software was tested on Vír I. catchment basin and the results of this probe were evaluated from viewpoints of air temperature, precipitation and discharge characteristics in the Dalečín measurement river cross section in distant future according to A1B SRES climate scenario, implemented in LARS-WG weather generator.
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Study and comparison of main kinds of evolutionary algorithms
Štefan, Martin ; Holeňa, Martin (advisor) ; Gemrot, Jakub (referee)
Evolutionary algorithms belongs among the youngest and the most progressive methods of solving difficult optimization tasks. They received huge popularity mainly due to good experimental results in optimization, a simplicity of the implementation and a high modularity, which is an ability to be modified for different problems. Among the most frequently used Evolutionary algorithms belongs Genetic Algorithm, Differential Evolution and Evolutionary Strategy. It is able to apply these algorithms and theirs variants to both continuous, discrete and mixed optimization tasks. A subject of this theses is to compare three main types of algorithms on the catalyst optimization task with mixed variables, linear constraints and experimentally evaluated fitness function.
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Evolutionary Optimization of Control Algorithms
Weisser, Roman ; Šeda, Miloš (referee) ; Zelinka,, Ivan (referee) ; Ošmera, Pavel (advisor)
The dissertation thesis deals with Evolution optimization of control algorithms. The first part of the thesis describes the principles and partial methods of evolution optimization methods especially those used in two-level transplant evolution method. Later the grammatical evolution method is described, which modified algorithm became impulse for creation of transplant evolution method. The transplant evolution method and its two-level modification are new evolutionary algorithms proposed in this work, which were used for optimization of structure and parameters of general controllers control algorithms. The transplant evolution algorithm and its extended two-level modification are described in detail in next chapters. The proper settings of evolutionary algorithms are important for minimization the time of optimization and for finds results approaching the global optimum. For proper setting the parameters of differential evolution was created meta-evolution algorithm that is described in chapter named meta-evolution. The basic concepts of control, chosen methods of system identification and controller parameters settings are described in next part. This part describes algorithms of digital controllers and some specific methods uses in digital control. The demonstrations of control algorithm optimizations of various types of controllers are showed in experimental part. The optimized algorithms of general controllers are compared with various types of PSD controllers which were set by various algebraic methods or differential evolution for various models of systems. In the conclusion of this work is stated a recommendation for further development of evolutionary optimization of controllers are focusing on parallel and distributed computing.
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Evolutionary algorithms
Haupt, Daniel ; Polách, Petr (referee) ; Honzík, Petr (advisor)
The first part of this work deals with the optimization and evolutionary algorithms which are used as a tool to solve complex optimization problems. The discussed algorithms are Differential Evolution, Genetic Algorithm, Simulated Annealing and deterministic non-evolutionary algorithm Taboo Search.. Consequently the discussion is held on the issue of testing the optimization algorithms through the use of the test function gallery and comparison solution all algorithms on Travelling salesman problem. In the second part of this work all above mentioned optimization algorithms are tested on 11 test functions and on three models of placement cities in Travelling salesman problem. Firstly, the experiments are carried out with unlimited number of accesses to the fitness function and secondly with limited number of accesses to the fitness function. All the data are processed statistically and graphically.
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Optimization of large technology compound design
Krňávek, Ondřej ; Kršík, Jakub (referee) ; Nevařil, Aleš (advisor)
This thesis deals with the optimization of the structural design of large technology compounds. The main emphasis is placed on the participation of available optimization instruments in the design of supporting structures of these constructions. The introductory part is primarily focused on the optimization itself. In this part are further specified also used optimization methods, computational finite element method, implemented code checks and calculation of cost of construction. The main part is dedicated to application of optimization procedure for the design of steel supporting structure of the auxiliary technological object of thermal power plant. The objective criterium shall then constitute the total cost of construction works along with operating costs. For the solution is used Scia Engineer software together with optimization module Scia Engineer Optimization Toolbox. The whole analysis is presented comprehensively from the description of computational model to results evaluation. The attention is paid to the optimization task settings, technical solution of optimization, optimization methods deployment and during the calculation process (especially to the development of objective function values and desing constraints during the optimization solution).
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Ingelligent Import of OSM into the Traffic Simulator TRASI
Muzika, Dávid ; Klusáček, Jan (referee) ; Honzík, Petr (advisor)
The thesis deals with the design and implementation of algorithms for import maps into the simulator TRASI. These algorithms are capable of import map from map portal OpenStreetMaps to the simulation environment. The work deals with adjusting the internal structure of the imported intersections, so that their structure was correct according to the rules of traffic. The work deals with the design and implementation of differential evolution for the design of the structure of intersections.
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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.
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