|
| |
|
| |
|
|
Genetic Algorithm Design for Distribution Network Outfits Optimalization
Ondruš, Tomáš ; Skala, Petr (referee) ; Paar, Martin (advisor)
The work deals with genetic algorithms and their potential use in application software to optimize high voltage switching elements of distribution network. Theoretical part explains the basic concepts of genetic algorithms such as a gene, population and chromosome and basic principles of the development of genetic algorithms.. The main task of the thesis is to design the algorithm that will simulate the distribution of the sectionalizers by telecontrolled section switches or reclosers and analyze how to set the the parameters affecting the convergence speed of genetic algorithm. The basic parameters affecting the convergence of breeding, mutation probability, population size or using of elitism. The second goal is finding a suitable set of input parameters for the selected population sizes without and with using elitism. The results of the work determine the most appropriate settings for each generation and determining the approximate number of generations needed to find the best solution. The genetic algorithm applocation was tested on a less extensive distribution network with six switching elements
|
|
|
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.
|
|
|
Evolutionary computing
Popelka, Jan ; Smékal, Zdeněk (referee) ; Karásek, Jan (advisor)
The aim of this Bachelor's Thesis was to get acquainted with the Evolutionary Optimization Techniques, mainly with the Genetic Algorithm and Genetic Programming. It was subsequently described the role of optimization problem TSP solved using Genetic Algorithms and other Chapter solving Symbolic Regression using Genetic Programming. This optimalization problems were created in the programming JAVA and there are solved practical part of the thesis.
|
|
|
Comparative and phylogenetic analysis of viruses in the University Hospital Brno
Švestková, Tereza ; Sedlář, Karel (referee) ; Nykrýnová, Markéta (advisor)
This thesis is focused on the SARs-CoV-2 coronavirus associated with severe acute respiratory syndrome, which was first identified in 2019. This coronavirus caused a pandemic that affected almost the entire world. Knowledge of the genetic information is needed for vaccine development, to determine infectivity and to predict the evolution of SARs-CoV-2 variants. To obtain genetic information, RNA must be sequenced and these genomic sequences must be assembled. By comparing the assembled genomes, it is possible to find out which part of the organism has mutated. Phylogenetic analysis is performed on the basis of the concordance or divergence in the assembled genomes, which indicates the evolution of the organism and shows the evolutionary relationship with other organisms. The practical part is focused on the assembly of genomes from samples from patients in the University Hospital Brno and evaluation of the quality of the assembly. After the genomes are assembled, the next goal is to evaluate the variability and subsequent phylogenetic analysis.
|
|
|
Discovery of Wireless Sensor Network Topology Using Genetic Algorithms
Dalecký, Štěpán ; Samek, Jan (referee) ; Zbořil, František (advisor)
The thesis deals with a design of the genetic algorithm that is able to discover the wireless sensor network topology using signal strength among particular sensors. At first, the thesis describes the theory of genetic algorithm and wireless sensor network. Subsequently, on the basis of this theory, the genetic algorithm serving for the wireless sensor network topology discovery has been designed. The thesis also describes important features of the algorithm implementation. In conclusion, the outcomes have been reviewed.
|
|
|
Methods to detect selection in DNA sequences
Procházka, Ondřej ; Maděránková, Denisa (referee) ; Škutková, Helena (advisor)
The topic of semestral thesis is methods to detect selection in DNA sequences. In the begining of the thesis we will describe molecular evolution. It will be written what made the evolution and how the evolution is shown. Moreover there are gen mutations and mechanisms of diffuse and fixation. It will be defined what pozitive, negative and neutral selection is. The thesis is focused on evolution distance of synonymous and nonsynonymous substitution. There will be described three methods – Nei-Gojobori, Li-Wu-Luo and Comeron. All these methods will be described with mathematic formulas. There will be statistic test to decide what kind of selection ti is – there will be used z-test. In the practical part, there will be information about developed software what counts selection pressure from sequences from databazes in format GenBank and it shows parts where selection is. The software will be used for two data sets with two different genetic codes. The result will be discussed. We will discuss results of all three methods of selection pressure and influence of input parametrs.
|
|
|
Predictor of the Effect of Amino Acid Substitutions on Protein Function
Musil, Miloš ; Martínek, Tomáš (referee) ; Bendl, Jaroslav (advisor)
This thesis discusses the issue of predicting of the effect of amino acid substitutions on protein funkcion, based on phylogenetic analysis method, inspired by tool MAPP. Significant number of genetic diseases is caused by nonsynonymous SNPs manifested as single point mutations on the protein level. The ability to identify deleterious substitutions could be useful for protein engineering to test whether the proposed mutations do not damage protein function same as for targeting disease causing harmful mutations. However the experimental validation is costly and the need of predictive computation methods has risen. This thesis describes desing and implementation of a new in silico predictor based on the principles of evolutionary analysis and dissimilarity between original and substituting amino acid physico-chemical properties. Developed algorithm was tested on four datasets with 74,192 mutations from 16,256 sequences in total. The predictor yields up to 72 % accuracy and in the comparison with the most existing tools, it is substantially less time consuming. In order to achieve the highest possible efficiency, the optimization process was focused on selection of the most suitable (a) third-party software for calculation of a multiple sequence alignment, (b) overall decision threshold and (c) a set of physico-chemical properties.
|
|
|
Prediction of the Effect of Nucleotide Substitution Using Machine Learning
Šalanda, Ondřej ; Martínek, Tomáš (referee) ; Bendl, Jaroslav (advisor)
This thesis brings a new approach to the prediction of the effect of nucleotide polymorphism on human genome. The main goal is to create a new meta-classifier, which combines predictions of several already implemented software classifiers. The novelty of developed tool lies in using machine learning methods to find consensus over those tools, that would enhance accuracy and versatility of prediction. Final experiments show, that compared to the best integrated tool, the meta-classifier increases the area under ROC curve by 3,4 in average and normalized accuracy is improved by up to 7\,\%. The new classifying service is available at http://ll06.sci.muni.cz:6232/snpeffect/.
|
guest ::
