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The Forecasting Model of Demand in the Textile Industry
Kunc, Tomáš ; Oulehla, Jiří (referee) ; Luňáček, Jiří (advisor)
Thesis is focused on forecasting methods and their comparison according to accuracy indicators. Forecast methods were utilized for building a forecast model of demand in texture industry. Usefulness of the thesis comes from forecasting an amount of demand in the future, which can be used by sellers, manufacturers and others impacted by amount of demand in textile industry. Thesis contains general reccomendations on forecasting process and helps with choice of appropriate methods of forecast.
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Application of Algorithms of Predictive Maintanence for RUL Estimation
Dvořák, Jan ; Brablc, Martin (referee) ; Dobossy, Barnabás (advisor)
The aim of this thesis is to acquaint the reader with the areas of predictive maintenance and its algorithms within its prognostic part. The remaining useful life of the system will be determined on the data sets and the performed experiment using prognostic models in accordance with the algorithms described in the research section. MATLAB and its other applications described in the work were used for data processing and modeling.
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Application of Algorithms of Predictive Maintanence for RUL Estimation
Dvořák, Jan ; Brablc, Martin (referee) ; Dobossy, Barnabás (advisor)
The aim of this thesis is to acquaint the reader with the areas of predictive maintenance and its algorithms within its prognostic part. The remaining useful life of the system will be determined on the data sets and the performed experiment using prognostic models in accordance with the algorithms described in the research section. MATLAB and its other applications described in the work were used for data processing and modeling.
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The Forecasting Model of Demand in the Textile Industry
Kunc, Tomáš ; Oulehla, Jiří (referee) ; Luňáček, Jiří (advisor)
Thesis is focused on forecasting methods and their comparison according to accuracy indicators. Forecast methods were utilized for building a forecast model of demand in texture industry. Usefulness of the thesis comes from forecasting an amount of demand in the future, which can be used by sellers, manufacturers and others impacted by amount of demand in textile industry. Thesis contains general reccomendations on forecasting process and helps with choice of appropriate methods of forecast.
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Machine learning-based approaches to forecasting international trade
Kovařík, Tomáš ; Semerák, Vilém (advisor) ; Macháček, Vít (referee)
In this thesis I focus on comparison of gravity model estimated with ordinary least squares and Poisson pseudo-maximum likelihood with regression techniques based on machine learning, namely support vector machines, random forests, and arti_cial neural networks. I discuss the advantages and disadvantages of these approaches and compare their forecasting accuracy on exports data. I demonstrate that random forest models and arti_cial neural networks provide superior forecasting accuracy.
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Quo Vadis, Slovakia? Context scenarios about the Environment of the Slovak Republic
Semberová, Anna ; Havranek, Miroslav (advisor) ; Nováček, Pavel (referee)
The main objective of the thesis is an analysis of possible future scenarios. This research is systematically focused on the analysis of the future possible trends in the context of the Slovak Republic's environment. The basis of the analysis is to identify the key external drivers and according to them to create the final scenarios of the future. The main approach to the scenario building in this thesis is the method of Cross-Impact Balance. Scenarios were created by semi-structured interviews with experts and by using the combinatorial analysis of consistency in terms of cross-impact of individual variants of the driving forces. The result of this thesis is five scenarios, referring to the future context of the environment of the Slovak Republic, depending on the development of a combination of different variants of external factors. For this scenarios there has been prepared the analysis of risks and opportunities in the perspective of the Environment of the Slovak Republic. Identified scenarios can be briefly described through the impact from least to the most positive. The first scenario shows the threat of an environmental collapse. The second scenario describes a power struggle over the resources and the consequences of excessive use of raw materials. The middle scenario describes the risk...
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Scenarios of future development of Manětínsko
Vaňková, Petra ; Rynda, Ivan (advisor) ; Havránek, Miroslav (referee)
Thesis is focused on one specific territory - Manětínsko and deals with the possibility of creating credible scenarios of its future development. Although our future will always remain hidden is important to consider its direction that we can expect, especially in today's world, where nature and environment are endangered on a global scale. Human society also stands on fragile basis/foundations and must face the economic and other crises. Therefore, it is important to think ahead about possible future development at all levels (local, regional and global) and to try to avoid events that could threaten the overall development/ the development progress. Scenarios are also an important tool for strategic planning and can offer different options for actions and decision making. The work is divided into theoretical and empirical part. The theoretical part deals primarily with the selected location itself and its most important characteristics. This part is an important basis for the empirical part, which besides other things is based on data obtained from interviews with selected respondents. Outline of these interviews arose on this theoretical basis. It was the 12 interviews that aimed to identify major problems and opportunities of Manětínsko, which will play role in the future development of the...
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Forecasting Mortgages: Internet Search Data as a Proxy for Mortgage Credit Demand
Saxa, Branislav
This paper examines the usefulness of Google Trends data for forecasting mortgage lending in the Czech Republic. While the official monthly statistics on mortgage lending come with a publication lag of one month, the data on how often people search for mortgage-related terms on the internet are available without any lag on a weekly basis. Growth in searches for mortgages and growth in mortgages actually provided are strongly correlated. The lag between these two growth rates is two months. Evaluation of out-of-sample forecasts shows that internet search data improve mortgage lending predictions significantly. In addition to forecasting performance evaluation, an experimental indicator of restrictively tight mortgage credit standards and conditions is proposed. Nowadays many countries run bank lending surveys to monitor the tightness of bank lending standards and conditions. The proposed indicator represents a complementary tool to such a survey.
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