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Web Simulator of Football Leagues and Championships
Urbanczyk, Martin ; Holkovič, Martin (referee) ; Hynek, Jiří (advisor)
This thesis is about the creation of a simulator of football leagues and championships. I studied the problematics of football competitions and their systems and also about the base of machine learning. There was also an analysis of similar and existing solutions and I took inspiration for my proposal from them. After that, I made the design of the whole simulator structure and of all of its key parts. Then the simulator was implemented and tested. The application allows simulating top five competitions in UEFA club coefficients rating.
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Lossless Light Field Compression
Navrátil, Robert ; Šolony, Marek (referee) ; Bařina, David (advisor)
This thesis is focused on lossless light-field images compression, where it could be viable to extend common predictors into more dimensions. First chapter is regarding to essential theory about light-field images and 4D light-field, which is followed by description of every predictor and coder. With this is connected description of used compression pipeline. Last chapters contains description of solution and differences between every predictor result and theirs dimensional variant. At the end the results are compared with PNG. The result is that some 4D variants of implemented predictors have better compression rate than PNG.
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Assessing Economic Situation of a Company and Proposals for Its Improvement
Matys, Jan ; Veselovský, Pavel (referee) ; Doubravský, Karel (advisor)
The diploma thesis evaluates the economic situation of BPS Bicycle Industrial s. r. o. time series analysis. The theoretical part describes financial indicators, time series analyzes and regression and correlation analysis. Based on the analyzes, suggestions were made to improve the current situation of the company. BPS has proven to be financially sound. Shortcomings to improvement were identified from the analyzes. For example, share of equity and debt, use of surplus funds and turnover of receivables and payables. This ratio needs to be addressed through greater use of debt. The system of sanctions is solution for problem the turnover of receivables and the use of surplus funds by investing in shares.
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The Use of Artificial Intelligence for Decision Making in the Firm
Seryj, Michal ; Budík, Jan (referee) ; Dostál, Petr (advisor)
Diploma thesis deals with design of a model for currency rate prediction by using artificial intelligence as a tool for decision making process in business and public administration. Concrete usage of this prediction is applied in company TechPlasty s.r.o. The thesis focuses on analysis of input data, optimization of a prediction model and evaluation of the results and their profit for the selected company.
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Tool for Classification of Lifestyle Traits Based on Metagenomic Data from the Large Intestine
Kubica, Jan ; Hon, Jiří (referee) ; Smatana, Stanislav (advisor)
This thesis deals with analysis of human microbiome using metagenomic data from large intestine. The main focus is placed on bacteria composition in a sample on different taxonomic levels regarding the lifestyle traits of an individual. For this purpose, a tool for classification of several attributes was created. It considers attributes like diet type and eating habits (vegetarian, vegan, omnivore), gluten and lactose intolerance, body mass index, age or sex. From range of machine learning perspectives considering K Nearest Neighbours (kNN), Random Forest (RF) and Support Vector Machines (SVM) were used. Datasets for training and final evaluation of the classifier were taken from American Gut project. The thesis also focuses on particular problems with metagenomic datasets like its multidimensionality, sparsity, compositional character and class imbalance.
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The Use of Artificial Intelligence for Decision Making in the Firm
Volný, Miloš ; Budík, Jan (referee) ; Dostál, Petr (advisor)
This thesis is concerned with future trend prediction on capital markets on the basis of neural networks. Usage of convolutional and recurrent neural networks, Elliott wave theory and scalograms for capital market's future trend prediction is discussed. The aim of this thesis is to propose a novel approach to future trend prediction based on Elliott's wave theory. The proposed approach will be based on the principle of classification of chosen patterns from Elliott's theory by the way of convolutional neural network. To this end scalograms of the chosen Elliott patterns will be created through application of continuous wavelet transform on parts of historical time series of price for chosen stocks.
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Air Quality Analysis in Office and Residential Areas
Tisovčík, Peter ; Korček, Pavol (referee) ; Kořenek, Jan (advisor)
The goal of the thesis was to study the indoor air quality measurement focusing on the concentration of carbon dioxide. Within the theoretical part, data mining including basic classification methods and approaches to dimensionality reduction was introduced. In addition, the principles of the developed system within IoTCloud project and available possibilities for measurement of necessary quantities were studied. In the practical part, the suitable sensors for given rooms were selected and long-term measurement was performed. Measured data was used to create the system for window opening detection and for the design of appropriate way of air change regulation in a room. The aim of regulation was to improve air quality using natural ventilation.
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Analysis of Data to Solve Problems with Humidity in Buildings
Nečasová, Klára ; Korček, Pavol (referee) ; Kořenek, Jan (advisor)
The aim of this work was to solve problems with excessive humidity in buildings using data analysis. The theoretical part of the work deals with impacts of excessive humidity on the health of building occupants and also the condition of the building structure. Data mining methods including classification, prediction, and clustering are described together with model evaluation and selection. The practical part focuses on hardware platform description and measurement scenarios. Key parameters affecting indoor relative humidity are indoor and outdoor temperature and outdoor relative humidity. The long-term measurement of the mentioned parameters was performed using the set of sensors and BeeeOn system. Measured data was used to design a system for event detection related to a humidity change. The approach to air change regulation in the room was based on natural ventilation.
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Speed of sound prediction
Řežábková, Jana ; Hartman, David (advisor) ; Brabec, Marek (referee)
This bachelor thesis presents a novel approach for speed of sound pre- diction in aqueous electrolytic solutions using machine learning techniques. A single model capable of accurately predicting the speed of sound in se- lected electrolytic aqueous solutions at different temperatures and molalities is trained. The machine learning experiment is designed to exploit the dis- sociation of electrolytes in water. Electrolytes are viewed as cation/anion pairs. Therefore, electrolyte description is based purely on its constituting ions. This approach allows to view the available data as a matrix in which rows represent cations, columns anions and each cell a full electrolyte. The idea of being able to fill cells for which no speed of sound data is yet avail- able is tested within the thesis. The final model's accuracy is compared to existent research on speed of sound prediction. However, some of the model approaches are novel and have no existing comparable settings. 1
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