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Determination of the performance of the cooling circuit - cooling tower
Velešík, Aleš ; Hanzal, Luděk (referee) ; Baláš, Marek (advisor)
The aim of this work is to determine the performance and description of the cooling circle in the cooling tower. In order to do that there was applied the linear regression approach in order to create structural empirical model of the cooling tower. The data obtained was analysed through QC expert software, which, if correct data applied, identifies suitable model for specific tower. The models created will be used for diagnostics of the cooling circles and as a comparison tool with other cooling towers in the future. Thus, the findings of this thesis are polynoms, which in thic technological setup characterise the models of the cooling towers.
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Statistical Modelling of Air Pollution by Dust Aerosol
Čampulová, Martina ; Karpíšek, Zdeněk (referee) ; Michálek, Jaroslav (advisor)
The diploma thesis deals with multivariate statistical methods and their environmental applications. The theoretical part is devoted to selected methods of linear regression analysis, method of principal components and the model of classical and robust factor analysis is also described. In the practical part of thesis, the main emission sources of PM1 aerosols in summer and winter period in Brno and Šlapanice are determined by using the classical factor analysis. The main aerosol emission sources in summer and winter in Šlapanice are also identified by using the robust factor analysis. Furthermore, the prediction of concentrations of PM1 aerosols in summer and winter period in Brno and Šlapanice is performed by using the linear regression model.
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Approximation function implementation into PIC microprocessor
Petřík, Tomáš ; Sysel, Petr (referee) ; Šmirg, Ondřej (advisor)
This bachelor‘s thesis deals with the implementation of approximation function into the PIC microprocessor. Thesis is focused on microprocessor architecture and analysis of approximation functions. Then for actual implementation is chosen the method of least squares, and because of its relative simplicity and accuracy in comparison with other methods. Microcontroller is using the A/D converter to measure the dependence of non-linear system, which is connected to the microprocessor. Measure the voltage on a logarithmic potentiometer, which represents non-linear system, depending on the position of the slider track resistance. Then, using the method chosen microprocessor calculates the characteristic non-linear system. The measured values are compared with the theoretical, calculated the chosen method. The values measured, and their theoretical difference is then displayed on the display, connected to the microprocessor. In conclusion, then discuss the results together with the possibility of further developing this work.
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Hedonic models on real estate market
Špesová, Nikola ; Zouhar, Jan (advisor) ; Bíza Bisová, Sára (referee)
Thesis is concerned with the Prague apartment prices. It compiles various econometric models determine that price under linear regression. It discusses the influence of individual factors such as size, number of rooms, floor, type of ownership, and so on. It focuses on three main hypotheses. The first is the floor impacts, which is proving to have a quadratic functional dependence. The second is a comparison of personal property with a cooperative and brick and panel construction. It turned out that the price difference between brick privately ownership and cooperative panel construction can be up to nearly 30 %. The last major hypothesis is the impact of time perspective between 2006 and 2013. The data shows that the financial crisis of the years 2007 - 2009 hit the Prague real estate market only on a small scale.
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Application of Phillips curves in the years 2011 - 2013 for selected countries of the European Union and the comparison with the Czech Republic
Šefara, Ivan ; Adámek, Petr (advisor) ; Sirůček, Pavel (referee)
The foundation for my senior thesis is based on the theoretical model of Phillips curve and its analysis which is aimed at defining the relationship between inflation and unemployment rates. The curve was constructed in order to determine the short- and long-term transformation periods in various economies. The Philips curve was modeled using linear regression and the interrelationship between previously mentioned inflation and unemployment rates is evaluated via correlation analysis. For this research, it was essential to gather and organize empirical and statistical data of Czech Republic and other chosen countries of the European Union. Further, I will examine the compiled statistical data for the Philips curve model and try to confirm the validity of the data.
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Neural Networks in R
Arzumanov, Eduard ; Bašta, Milan (advisor) ; Žižka, David (referee)
The aim of this work was to present the issue of neural network, which is still, despite the fact it exist and has been applied for several years, remains quite unknown for a considerably big part of public and academical environment. The aim of the practical part was to verify via practical application if neural network are truly a better instrument of statistical analysis, than the commonly used ones, especially when the goal is to analyze and describe complex processes and relationships between them. Further aim of the work was to investigate and describe the relationships between the development of trading volumes of Apple shares and the shares of competitive companies regarding the market of smart phones such as Google, HTC, Nokia, Samsung using neural network models. The attainment of these goals was realized through a rather extensive description of neural networks theory as well as the presentation of valuable theoretical tools for avoiding the frequent barriers occurring during the practical implementation. This practical application was realized via software called R, which has widely spread lately due to its availability and a vast range of flexibility, which is provided to users. The value of this work is familiarization and the creation of an integrated knowledge within readers about the issue of neural networks and the deliverance of a proof, that neural networks are indeed a better tool compared to the commonly used ones (ARMA models, linear regression). The author of the work gained a lot of useful knowledge about neural networks, learned how to use them in practice especially in the environment of R software, by which he shifted his proficiency with the current software to a whole new level.
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Productivity and its measuring aiming at individual size categories of companies.
ŘÍHA, Jaroslav
The main aim of this thesis was to assess the relation between productivity and size of company in selected sector of national economy construction industry. The sub-objectives were determined as follows: to gather theoretical information on the topic, to analyse the productivity according to the individual size categories of companies in the selected sector, to assess the relation between the size of company and the productivity and to ascertain the level of productivity in the Czech Republic in comparison with the selected sector.
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Highly Robust Estimation of the Autocorrelation Coefficient
Kalina, Jan ; Vlčková, Katarína
The classical autocorrelation coefficient estimator in the time series context is very sensitive to the presence of outlying measurements in the data. This paper proposes several new robust estimators of the autocorrelation coefficient. First, we consider an autoregressive process of the first order AR(1) to be observed. Robust estimators of the autocorrelation coefficient are proposed in a straightforward way based on robust regression. Further, we consider the task of robust estimation of the autocorrelation coefficient of residuals of linear regression. The task is connected to verifying the assumption of independence of residuals and robust estimators of the autocorrelation coefficient are defined based on the Durbin-Watson test statistic for robust regression. The main result is obtained for the implicitly weighted autocorrelation coefficient with small weights assigned to outlying measurements. This estimator is based on the least weighted squares regression and we exploit its asymptotic properties to derive an asymptotic test that the autocorrelation coefficient is equal to 0. Finally, we illustrate different estimators on real economic data, which reveal the advantage of the approach based on the least weighted squares regression. The estimator turns out to be resistant against the presence of outlying measurements.
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