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Mathematical Modelling of Relation between Economic Quantities
Žigárdy, Martin ; Hřebíček, Jiří (referee) ; Chvátalová, Zuzana (advisor)
My work is aimed on creating and on subsequent economical interpretation of mathematical models presenting relations of continual development of PX index (Czech stock index) and continual developments of five important world titles, which are price of the West Texas Intermediate Crude Oil barrel, exchange rate between Dollar and Czech Crown as well as Euro and Czech Crown and indexes DAX (German stock index) and Dow Jones (American stock index). The models are create by using regression analysis and by mathematical software Maple version 12
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Program for Analyzing Economical Data via Mathematical Modeling in Maple
Žigárdy, Martin ; Hřebíček,, Jiří (referee) ; Chvátalová, Zuzana (advisor)
In this diploma thesis I constructed generally usable program for processing economical data through mathematical methods of linear regression in Maple system. Program is used for trend dependency analysis of examined quantities. Via multi-stage algorithmization and implementation of information criterion I created interactive form with user-friendly interface with possibility of straight data import from office suite applications. Functionality of this program is verified on example with specific data collection.
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Experimental determination of the relationship between NDT parameters and the compressive strength of concrete
Kozáček, Vojtěch ; Komárková, Tereza (referee) ; Kocáb, Dalibor (advisor)
The diploma thesis deals with non-destructive testing of concrete as well as with the relationship between determined parameters and the compressive strength of concrete. The thesis is mainly focused on the ultrasonic pulse velocity method and the rebound hammer test. The experimental part of the thesis describes non-destructive tests performed on concrete blocks. The compressive strength was tested on the drill cores taken from the concrete blocks. The aim of this thesis is to find regression models of the relationship between the compressive strength and non-destructive parameters, and the subsequent analysis of the results.
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The Model of the Cost Function of the Bulding Factory Standan s.r.o,
Jamborová, Daniela ; Oulehla, Jiří (referee) ; Luňáček, Jiří (advisor)
The main goal of the bachelor's thesis is to determine the cost functions of the contract of the construction company Standan s. r. o.. The sub-objectives of the thesis are to define the theoretical basis of the solution, to perform a classification analysis and to define the cost function of the order. The last partial objective is to identify the key parameters of the cost function and their relationship with the total price of the order through correlation and regression analysis.
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Regression methods for statistical analysis of spatial data
Klimprová, Lucie ; Šerák, Petr (referee) ; Michálek, Jaroslav (advisor)
Kriging techniques are regression methods used for evaluation of continuous spatial processes. If the covariance structure of process is unknown, then it's necessary to estimate it from the data. The first part of this Master's thesis is devoted to description the kriging method and to estimate of a variogram fuction, which describes the covariance structure of considered process. The second part includes the implementation of kriging method in MATLAB for simulated and real data.
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Significance of different financial ratios in predicting stock returns: NYSE - cross-industry analysis
Coufal, Matěj ; Mejstřík, Michal (advisor) ; Kurka, Josef (referee)
The goal of this research is to investigate the power of following seven variables to predict stock returns on the New York Stock Exchange: price to earnings ratio (P/E), dividend yield (DY), debt to equity ratio (D/E), book to market ratio (B/M), return on assets (ROA), return on equity (ROE) and market capitaliza- tion (MC). Companies selected for the analysis are divided into five industries (airlines, computers and software, financial services, food and beverages, energy) which enables to observe the difference between the sectors as far as the statistical significance of regressors is concerned. The ability of six financial ratios and MC to forecast stock returns is examined between February 2010 and February 2020, whereas three investment horizons are considered: three months, one year, three years. Panel data regression models reveal different significant variables for each industry and show that the strength of the relationship between these regressors and expected stock returns increases with a longer investment horizon.
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Econometric Modelling of Natural Gas Consumption in the Electricity Sector in the Midwest Europe Region
Kunc, Tomáš ; Michalíková, Eva (referee) ; Doubravský, Karel (advisor)
The thesis deals with econometric modeling of natural gas consumption within the electricity industry for the purpose of electricity production. The first part of the thesis focuses on theoretical foundations, describing the electricity market and econometric modeling, with a particular focus on regression analysis. In the analytical part, this knowledge is applied to the selection and adjustment of potential factors. As part of the proposed solution, a regression model is constructed that describes natural gas consumption in electricity production as a function of selected factors. The predictive ability of the model is verified using data from a testing period.
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Sparse Representation of Signals
Mesárošová, Michaela ; Arm, Jakub (referee) ; Jirgl, Miroslav (advisor)
People who are immobile or lie for long periods are at high risk of developing pressure ulcers and require additional care. Therefore, it is necessary to monitor the condition of such persons as simply and efficiently as possible. In this work, we focus on processing the signals provided by a pressure mattress with a 30x11 sensor grid on which a person lays and the possibilities of its use after conversion into sparse representation coefficients. Redundant dictionaries, also known as frames, enable non-orthogonal representation of signals, which leads to a sparse representation of coefficients. Since this approach provides many advantageous properties and is being used in various applications, such as denoising, segmentation, robust transformations, quantum theory, and others, we verified the possibility of classifying a person’s lying position based on a sparse representation. The results were compared with other traditional classification methods, which were found to be less suitable for the classification problem, with the best-achieved result of 92.41 % for CNN, but with high demands on time, design and complexity. The success rate of the classification reached 92.76 %, with fewer demands on design and implementation complexity. The possibilities of classification and reconstruction of an image containing occlusions were also investigated, where the sparse representation proved to be an effective method to remove these defects.
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