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Application of consumption function on CR
Poncar, Jaroslav ; Hušek, Roman (advisor) ; Formánek, Tomáš (referee)
Consumer function is a standard instrument of quantitative economic analysis to examine the relationship between consumer expenditure and income or other influencing factors such as liquid assets, interest rates or various demographic and social factors. In this thesis are presented the most frequently used methods in econometric analysis of consumption function. Attention is paid to the hypothesis of absolute income, relative income, life cycle, permanent income, rational expectations and consumption function based on the error correction model. Furthermore, the suitability of individual models for the current economic situation in the Czech Republic is assessed. Subsequently an empirical model of consumption function for the Czech Republic is designed and tested. Furthermore, the estimates of each consumption function model for the period before and after economic crisis of 2008-2009 are performed and compared. Finally, a short-term prediction of the consumption of Czech households is made.
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Computational Intelligence for Financial Market Prediction
Řeha, Filip ; Pilát, Martin (advisor) ; Mráz, František (referee)
Financial markets are characterized by uncertainty, which is associated with the future progress of world economics and corporations. The ability of an individual to forecast future market behaviour at least to a certain extent would give him an important competitive advantage on the market. The aim of this work is to explore neural networks and genetic programming as possible tools which could be used for financial markets forecasting and apply them on historical financial data. Experiments using neural networks and genetic programming were performed and the results show, that both tools can be employed successfully. On average, neural networks outperformed genetic programming in our experiments. In order to evaluate and visualize the results of our created strategies, the MarketForecaster application was implemented. Powered by TCPDF (www.tcpdf.org)
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Template-based RNA tertiary structure prediction
Galvánek, Rastislav ; Hoksza, David (advisor) ; Jelínek, Jan (referee)
The thesis deals with proposal, implementation and testing of a new algorithm for homologous tertiary RNA structure prediction, which means using a structure similar to the template. It focuses on the possibility of large RNA structures prediction in reasonable time and precision. The algorithm is based on copying conserved parts of template structure into the target structure. The unconserved parts are then predicted by an existing ab initio algorithm. The thesis is divided into four chapters. The first one contains basic information about RNA and its importance. The second one describes different ways of RNA prediction and it contains an overwiev of currently available prediction methods. The third one describes the invented algorithm and the fourth one presents achieved results.
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Deep neural networks and their application for economic data processing
Witzany, Tomáš ; Mrázová, Iveta (advisor) ; Křen, Tomáš (referee)
Title: Deep neural networks and their application for economic data processing Author: Bc. Tomáš Witzany Department: Department of Theoretical Computer Science and Mathematical Logic Supervisor: Doc. RNDr. Iveta Mrázová, CSc., Department of Theoretical Com- puter Science and Mathematical Logic Abstract: Analysis of macroeconomic time-series is key for the informed decisions of national policy makers. Economic analysis has a rich history, however when considering modeling non-linear dependencies there are many unresolved issues in this field. One of the possible tools for time-series analysis are machine learn- ing methods. Of these methods, neural networks are one of the commonly used methods to model non-linear dependencies. This work studies different types of deep neural networks and their applicability for different analysis tasks, including GDP prediction and country classification. The studied models include multi- layered neural networks, LSTM networks, convolutional networks and Kohonen maps. Historical data of the macroeconomic development across over 190 differ- ent countries over the past fifty years is presented and analysed. This data is then used to train various models using the mentioned machine learning methods. To run the experiments we used the services of the computer center MetaCentrum....
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Electricity market: Analysis and prediction of volatility
Kunc, Vladimír ; Krištoufek, Ladislav (advisor) ; Hájek, Jan (referee)
Electricity market: Analysis and prediction of volatility Abstract Vladimír Kunc July 30, 2015 The last two decades can be characterized by restructuring of energy industry and the creation of new, competitive energy markets, where accurate forecasts of elec- tricity prices and price volatility are valuable both to consumers and producers. The aim of this work is to analyse several models for prediction of the price volatility of electricity on the Czech Electricity Day-ahead market on price data provided by OTE, a.s. for years 2009-2014. This work compares 144 different models' configura- tions for three distinct classes of models - autoregressive models, GARCH models, and artificial neural network models. This work provides comparison based on five different criteria, each describing the model in different way. Keywords: price prediction, volatility prediction, GARCH, neural networks, LSTM 1
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Prediction of type 1 diabetes mellitus by expression profile of peripheral leukocytes
Šornová, Veronika ; Kotrbová - Kozak, Anna Katarzyna (advisor) ; Daňková, Pavlína (referee)
Background: Type of 1 diabetes (T1D) is an autoimmune disease in which the cells of immune system attack the β-cells of pancreas. Consequently, destroyed β-cells do not produce insulin to reduce blood sugar levels. This disease is very complex, the pathogenesis is contributed by both genetic factors and environmental factors. In recent years, the number of individuals with T1D is increasing worldwide. Aims: The aim of this thesis was to investigate whether it is possible to predict T1D based on the expression profile of BACH2, CDC20, IGLL3P, EIF3A and TXNDC5 genes , which are involved in the development of immune system cells and insulin production. Another aim was to compare the expression of selected genes in children, in which the first detection of the disease may be done, and adults who suffer from prolonged T1D. The final goal was to compare the expression of individual selected genes in the HLA risk alleles DR04, DR03, DQA*05:01 a DQB*03:02. Methods: The DNA and RNA of patients with T1D and healthy individuals was isolated from blood. DNA was used to HLA genotyped. Isolated RNA was reverse transcribed into cDNA and then used in real-time PCR to determine the relative levels of gene expression. Conclusion: Significant results were obtained when the expression of BACH2, CDC20 and TXNDC5 genes...
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Analysis of endurance indicators in selected tests in relation to continuous and intermittent loading
Kotas, Jan ; Malý, Tomáš (advisor) ; Bunc, Václav (referee)
Title Analysis of the endurance indicators in selected tests in relation to continuous and intermittent loading Objectives The aim of this study was to examine the accuracy of the prediction formulas for indirect estimation VO2max from performances in the field tests. The criterion for comparing estimated values were results from laboratory spiroergometry test. Methods Ten physically active males (24,5 ± 2,5 years, 179,5 ± 6,2 cm, 75,8 ± 4,9 kg, BMI 23,5 ± 1,3 kg/m2 ) performed four different test sessions. Laboratory treadmill test was used for the direct measurement of the maximal oxygen consumption (VO2max) and three field tests for indirect estimation of the VO2max (Cooper test, Yo-Yo Intermittent Recovery Test Level 1 and 2). All the performances from field tests were calculated using prediction formulas. Results Directly measured values of VO2max during laboratory testing were in average 58,24 ± 2,77 ml.kg-1 .min-1 . Indirectly estimated values of VO2max from performances in the Cooper test were in average 61,15 ± 3,73 ml.kg-1 .min-1 , in Yo-Yo IRT1 52,46 ± 2,51 ml.kg-1 .min-1 and in Yo-Yo IRT2 53,19 ± 1,56 ml.kg-1 .min-1 . There was found large positive correlation between laboratory testing and Cooper test (r = 0,76). This correlation was the only one statistically significant. The...
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Analysis of occurrence of extremal values in time and space
Starý, Ladislav ; Volf, Petr (advisor) ; Dvořák, Jiří (referee)
This thesis describes and compares methods for statistical modeling of spatio- temporal data. Methods are extended by examples and numerical studies on real world data. Basic point of interest is statistical analysis of spatial data with unknown correlation structure and known position in space. Further analysis is focused on spatial data with temporal component - spatio-temporal data. Fi- nally, extremal values and their occurrences are discussed. The main aspiration of my thesis is to provide statistical tools for spatio-temporal data and analysis of extremal values of prediction. 1
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Analysis of general and specific physical conditioning tests in youth Nordic skiers and biathletes
Korbelář, Tomáš ; Sucharda, Jan (advisor) ; Gnad, Tomáš (referee)
Title: Analysis of general and specific physical conditioning tests in youth Nordic skiers and biathletes. Goal: The goal of thesis is judge the validity of individual general and specific physical conditioning tests in 2012, 2013 and 2014 and compare this way the youth categories in Nordic skiing and biathlon. Methods: From the test results of general and specific physical conditioning tests and results of the czech cup youth ranking as an index fo achievement in Nordic skiing and biathlon we did a correlation analysis to figure out the extent of dependence. With the help of correlation analysis we came to the conclusion that the tests in biathlon show stronger correlation to achievement than tests in Nordic skiing. Nordic skiing, biathlon, czech cup ranking, youth - male, female, correlation, coefficient, test sets, achievement, prediction, train-ability Results: Keywords:
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The Risk Assessment for Development of Acute Coronary Syndrome Based on Non-invasive Examinations
Elšíková, Kristýna ; Kovárník, Tomáš (advisor) ; Večeřová, Alena (referee)
Predikce rizika rozvoje akutního koronárního syndromu na základě neinvazivních vyšetření ABSTRACT The aim of presented diploma thesis coming out of the project held by II. interní klinika Všeobecná fakutní nemocnice v Praze is to determinate the risk assessment for development of acute coronary syndrome based on non-invasive examinations - intracoronary ultrasound, retinal arteries examination, biochemical markers of atherosclerosis and selected genes polymorphism. The thesis is divided into two main parts. The first part is theoretical and it consists of three chapters, the second part is analytical and it contains the research. The theoretical part gives concise information about the acute coronary syndrome, essential part focuses on atherosclerosis as a pathophysiologic base of this syndrome, risk factors, and stratification of cardiovascular risk which proved to be insufficient are as well mentioned. Next part describes a non-invasive coronary arteries examinations focusing on presented research. The last chapter of the theoretical part focuses on invasive coronary arteries examinations. The research part describes design and purpose of the project - the identification the high risk for development of acute coronary syndrome patients irrespective of the risk coming out standard evaluation models, and...
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