|
|
Functional Annotation of Nucleotide Polymorphism Using Evolution Strategy
Šalanda, Ondřej ; Martínek, Tomáš (referee) ; Bendl, Jaroslav (advisor)
This thesis brings a new approach to the prediction of the the effect of amino acid substitution. The main goal is to create a new meta-tool, which combines evaluations of eight already implemented prediction tools. The use of weighted consensus over those tools should lead to better accuracy and versatility of prediction. The novelty of developed tool lies in involving evolution strategy with experimentally defined parameters as a way to determine the best weight distribution. At the end, a complex comparison and evaluation of results is given.
|
|
|
Quantum-Inspired Optimisation Algorithms
Kosík, Dominik ; Sekanina, Lukáš (referee) ; Bidlo, Michal (advisor)
The focus of this work is an implementation of the chosen quantum-inspired optimisation algorithm and its modifications, which will be compared at the end of the work. As the optimisation algorithm was chosen simulated quantum annealing algorithm. The first part of the work will lay the theoretical groundwork of standard optimisation algorithms used in this work, physics from which the inspiration for the simulated quantum annealing originates, and a description of the chosen algorithm. The second part will focus on the implementation of the algorithms on the selected problems. The selected problems are travelling salesman problem, searching rules for cellular automaton and MAX-SAT problem. The last part will contain the proposed modifications of the simulated quantum annealing, a comparison of the basic variant and standard optimisations algorithms, and an evaluation of the results.
|
|
|
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.
|
|
|
Evolutionary Optimisation of Analogue Circuits
Mihulka, Tomáš ; Zachariášová, Marcela (referee) ; Bidlo, Michal (advisor)
The aim of this work was to create a system for optimisaton of specific analog circuits by evolution using multiple fitness functions . A set of experiments was run, and the results analyzed to evaluate the feasibility of evolutionary optimisation of analog circuits . A requirement for this goal is the study and choice of certain types of analog circuits and evolutionary algorithms . For the scope of this work , amplifiers and oscillators were chosen as target circuits , and genetic algorithms and evolutionary strategies as evolutionary algorithms . The motivation for this work is the ongoing effort to automate the design and optimisation of analog circuits , where evolutionary optimisation is one of the options .
|
|
|
The Impact of Candidate Solution Mappings on Evolutionary Algorithm Efficiency
Hrbáček, Jiří ; Korček, Pavol (referee) ; Křivánek, Jan (advisor)
The Concern of the present study is summarizing knowledges in the theory of mapping candidate solutions , analysis and application of evolutionary algorithms. The study provides summary of the evolutionary algorithms, classification and application. The target of the study is links gained knowledge from sectionS of ; evolutionary algorithms, mapping candidate solutions and creations of a system that will demonstrate and influence mapping the efficiency of the evolutionary algorithms succesfully.
|
|
|
Evolutionary Prediction of Time Series
Křivánek, Jan ; Bidlo, Michal (referee) ; Sekanina, Lukáš (advisor)
This thesis summarizes knowledge in the field of time series theory, method for time series analysis and applications in financial modeling. It also resumes the area of evolutionary algorithms, their classification and applications. The core of this work combines these knowledges in order to build a system utilizing evolutionary algorithms for financial time series forecasting models optimization. Various software engineering techniques were used during the implementation phase (ACI - autonomous continual integration, autonomous quality control etc.) to ensure easy maintainability and extendibility of project by more developers.
|
|
|
Advanced Evolutionary Image Filtering
Saranová, Ivana ; Drábek, Vladimír (referee) ; Bidlo, Michal (advisor)
This work aims to use cellular automata with a transition function of conditionally matching rules designed by the evolution strategy for the removal of noises of different types and intensities from digital images. The proposed method improves the original concept of conditionally matching rules by modifying the right side of the rule, extending it from a single value to a selection of functions. Furthermore, various evolution strategy setups were explored, including usage of different noise models for evolution, training on partially damaged images, and other setups, resulting in high-quality filters for each noise model. Comparing these filters to the existing methods shows great improvement from the original approach and the ability to evolutionarily design filters that are placed among the top methods quality-wise.
|
|
|
Quantum-Inspired Optimisation Algorithms
Kosík, Dominik ; Sekanina, Lukáš (referee) ; Bidlo, Michal (advisor)
The focus of this work is an implementation of the chosen quantum-inspired optimisation algorithm and its modifications, which will be compared at the end of the work. As the optimisation algorithm was chosen simulated quantum annealing algorithm. The first part of the work will lay the theoretical groundwork of standard optimisation algorithms used in this work, physics from which the inspiration for the simulated quantum annealing originates, and a description of the chosen algorithm. The second part will focus on the implementation of the algorithms on the selected problems. The selected problems are travelling salesman problem, searching rules for cellular automaton and MAX-SAT problem. The last part will contain the proposed modifications of the simulated quantum annealing, a comparison of the basic variant and standard optimisations algorithms, and an evaluation of the results.
|
|
|
Evolutionary Design of Quantum Operator
Kraus, Pavel ; Mrázek, Vojtěch (referee) ; Bidlo, Michal (advisor)
The goal of this thesis is to utilize various evolutionary algorithms for quantum operator design in the form of unitary matrices in direct representation. Evolution strategy, differential evolution, Particle Swarm Optimization and artificial bee colony algorithms were chosen. In this thesis, the third and fourth algorithms were used for the first time in relation to quantum operator design. The experiments have shown that the utilization of direct representation gives results of acceptable quality.
|
|
|
Evolutionary Optimization of Freight Transportation
Beránek, Michal ; Drahošová, Michaela (referee) ; Bidlo, Michal (advisor)
The following thesis deals with optimization of freight transport planning. The goal is to minimize expenses connected to transportation, which emerge from travelled distance. The expenses can be heavily reduced, if the routes are correctly planned, especially when there is a large number of customers to be served. This thesis focuses on solving the problem by using the evolutional algorithms, that are optimization methods based on principles of evolution. Thesis concentrates on Heterogeneous Fixed Fleet Vehicle Routing Problem. Thesis introduces multiple evolutional algorithms and their results are compared. The best algorithm, evolutional strategy with local neighbourhood search, achieves similar, for certain tasks even better results, than other existing evolutional algorithms, created to solve given problem.
|
guest ::
