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USE OF AUTOMATIC COLLECTION OF GROUND CONTROL POINTS FOR ORIENTATION OF ARCHIVAL AERIAL IMAGERY USING EXISTING DATA SETS
Berka, Rostislav ; Potůčková, Markéta (advisor) ; Dušánek, Petr (referee)
USE OF AUTOMATIC COLLECTION OF GROUND CONTROL POINTS FOR ORIENTATION OF ARCHIVAL AERIAL IMAGERY USING EXISTING DATA SETS Abstract The diploma thesis is focused on the automated searching of ground control points (GCPs) for processing archival aerial images (AAIs) and creating orthomosaics. The study evaluates selected computer vision operators (SIFT, SURF, ORB and image correlation) and various approaches for identifying and subsequently matching identical points between the reference dataset (current orthophoto) and AAIs. Thanks to AAIs georeferences, the searching area in AAI is known for finding the corresponding point to the reference one (from current orthophoto). Unfortunately, the georeferencing of AAIs provided by the Czech Office for Surveying, Mapping, and Cadastre (ČÚZK) was methodologically incorrect (very bad accuracy) and it had to be corrected before automated GCPs searching. The topic was supported by ČÚZK and datasets (current orthophoto, AAIs, ZABAGED vector data) were provided for processing purposes free of charge (beyond the standard student license). Based on operator testing, a fully automated methodology was developed in Python, relying on image correlation. The input includes AAIs, current orthophoto and a road network, with road intersections as reliable and time invariant points....
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Assessing Economic Situation of a Company and Proposals for Its Improvement
Hynek, Jan Jaroslav ; Franková, Tereza (referee) ; Doubravský, Karel (advisor)
The master’s thesis deals with the assessment of the financial situation of XZY s.r.o. using financial analysis and statistical methods. The theoretical part is divided into financial and statistical theory. In these parts, it presents the definition of selected financial ratios and statistical methods, which include time series regression and correlation analysis. The theoretical part is followed by an analytical part in which the financial situation of the selected company is evaluated along with the prediction of selected ratios. Furthermore, the selected ratios are subjected to correlation analysis where the interdependence between them is examined. The paper concludes with suggestions for improving the financial situation of the enterprise.
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Assessing Economic Situation of a Company and Proposals for Its Improvement
Rybár, Tomáš ; Novotná, Veronika (referee) ; Doubravský, Karel (advisor)
The diploma thesis focuses on the assessment of the economic situation of Prefa Brno a.s. and possible suggestions for improving its performance. The theoretical part of the thesis is devoted to the explanation of the concepts of financial and statistical analysis. These concepts are then applied in the analytical part. From the financial analysis, the difference and ratio indicators are evaluated, supplemented by a set of indicators. Regression analysis is performed on selected ratios with a forecast for the following period and correlation analysis is used to identify the interrelationships between them. Conclusions are drawn from the results, which are used to formulate possible measures to improve the current economic situation of the entity under study.
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Assessing Economic Situation of a Company and Proposals for Its Improvement
Pokorný, Dominik ; Fuchs, Ondřej (referee) ; Doubravský, Karel (advisor)
The thesis deals with the assessment of the economic situation of CQQ in the years 2013–2022 based on the results of selected financial analysis indicators and statistical methods. The theoretical part of the thesis focuses on financial and statistical theory. The analytical part contains calculations of financial indicators of the company, some of which are further processed in the statistical analysis. The last part is devoted to the proposed solutions for correcting or improving the economic situation of the company.
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Assessing Economic Situation of a Company and Proposals for Its Improvement
Rýpal, Matěj ; Novotná, Veronika (referee) ; Doubravský, Karel (advisor)
This thesis focuses on the evaluation of the economic situation of the company GUMEX, spol. s.r.o. and the prediction of future development using statistical methods. The theoretical part of the thesis deals with the description of selected financial ratios and statistical methods such as time series analysis, regression and correlation analysis. In the practical part, the individual ratios are calculated to assess the financial condition of the analysed company and the selected ratios are then analysed using statistical methods to predict future developments. The final part of the thesis is devoted to the proposals based on the results of the analytical part of the thesis and aimed at improving the financial situation of the company.
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Analysis of economic data using statistical methods
Pavlásek, Boris ; Doubravský, Karel (referee) ; Michalíková, Eva (advisor)
This bachelor thesis deals with the analysis of the economic data of a company and the subsequent evaluation of its financial situation. In doing so, it uses the tools of financial analysis and statistical methods, namely regression analysis and time series. The theoretical part presents the theory needed to perform the analysis and also explains different financial indicators, statistical methods and regression functions. In the analytical part, data from the company's financial statements are used for financial analysis and subsequent forecasting of their future progress. In the last parts of the thesis, a comprehensive assessment of the financial situation of the company and suggestions for solving the identified problems are presented.
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Classifier of traffic states and detectors
Březina, Ondřej ; Richter, Miloslav (referee) ; Janáková, Ilona (advisor)
The work deals with the description of sources of traffic data and methods of analysis of these data. Furthermore, states for the classification of traffic and detectors in the MATLAB environment are designed and implemented in the work. Finally, traffic flow models are modeled, which can also be used for traffic flow prediction.
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Financial time series analysis based on innovative Machine Learning Signal Processing approaches
Tshiangomba, Reagan Kasonsa ; Sehnalová, Pavla (referee) ; Cicone, Antonio (advisor)
Prognózování finančních časových řad bylo klasifikováno jako jeden z nejnáročnějších problémů v v posledním desetiletí kvůli jeho nestacionaritě a nelineárním vlastnostem. Na jednu stranu statistická techniky byly shledány neschopnými přesně předpovídat finanční časové řady. Na druhé straně techniky strojového učení dosáhly pozoruhodných výsledků, ale neposkytují explicitní způsob zacházení s nestacionární vlastností finančních časových řad. Navrhovaný přístup využívá schopnosti dekompozičních technik zpracování signálu k řešení nestacionární vlastnost finančních časových řad. Použitá technika rozkladu signálu v této práci je iterativní filtrování (IF), které generuje funkce vnitřního režimu (IMF). Tyto generované IMF spolu s původním signálem se používají k vytvoření časově-frekvenční reprezentace finanční časové řady zvané IMFogram. Dva typy údajů, jmenovitě MMF a IMFogram, se používají k trénování fúzní neuronové sítě pro predikci finančních časových řad. Jeden záznam součástí fúzní neuronové sítě je umělá neuronová síť (ANN), která bere jako MMF vstup. Další vstupní složkou fúzní neuronové sítě je konvoluční neuronová síť (CNN), která bere jako vstup IMFogram. Výstupy ANN a CNN jsou zřetězeny pro regresní úlohu. Ukážeme aplikaci tohoto nově vyvinutého přístupu k finančním datům, Abych byl přesný, série NASDAQ. A podáváme zprávy o jeho výkonu v různých scénářích hranic podmínky.
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