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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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Systém pro automatický návrh hasičských vozidel
KOTNOUR, Tomáš
The topic of this master´s is development of system for configuration of fire trucks. The design of the fire truck is based on legislative requirements, future incidents and the character of landscape. Processing of current incidents and how to predict future incidents is describe in next chapters. For prediction of the future incidents are used neural networks described the thesis. The main outcome of the thesis is implemented application designed for Windows platform.
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Solution of unemployment of young people through closer connestion of their vocational training with labor market requirements
Steindlberger, Martin ; Kotrusová, Miriam (advisor) ; Hiekischová, Michaela (referee)
This diploma thesis deals with the relationship between the vocational training of young people and the requirements of the labour market. The thesis is focused on secondary vocational education. The problem, that has been examined, is the lack of readiness of school graduates, to move to the free labour market. In order to improve this, it is necessary to try to reconcile the content and outputs of vocational training with the needs of the labour market. If graduates are poorly prepared for employers' needs, these graduates may become unemployed. The problem is getting worse with the longer duration of unemployment. The aim of this diploma thesis is to find out and describe who participates in vocational training and how their mutual cooperation is implemented. In the thesis the author will try to find out the strengths and weaknesses of this cooperation. He will also try to find out in what kind of way the training of young people to the needs of the labour market is adapted. The thesis is a case study focused on the South Bohemian Region, which is briefly presented by selected indicators characteristic of the selected region. To obtain the necessary data, there are used figures and statistics from the former researches, as well as information from selected participants involved in the solution...
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Předpovídání trendů akciového trhu z novinových článků
Serebryannikova, Anastasia ; Kuboň, Vladislav (advisor) ; Vidová Hladká, Barbora (referee)
In this work we made an attempt to predict the upwards/downwards movement of the S&P 500 index from the news articles published by Bloomberg and Reuters. We employed the SVM classifier and conducted multiple experiments aiming at understanding the shape of the data and the specifics of the task better. As a result, we established the common evaluation settings for all our subsequent experiments. After that we tried incorporating various features into the model and also replicated several approaches previously suggested in the literature. We were able to identify some non-trivial dependencies in the data which helped us achieve a high accuracy on the development set. However, none of the models that we built showed comparable performance on the test set. We have come to the conclusion that whereas some trends or patterns can be identified in a particular dataset, such findings are usually barely transferable to other data. The experiments that we conducted support the idea that the stock market is changing at random and a high quality of prediction may only be achieved on particular sets of data and under very special settings, but not for the task of stock market prediction in general. 1
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