|
|
Development of oil and the impact on modern society
Khlyustova, Anastasia ; Cibulka, Jakub (advisor) ; Janda, Karel (referee)
The aim of this thesis entitled Development of oil and the impact on modern society is to analyze the evolution of oil prices, to describe the factors affecting it, identify strengths and weaknesses, and try to dismantle existing models of prediction. The important part is the valuation of the forecasts. Selected problem is solved using data and models provided by large institutions such as the IMF, World Bank, etc. Final summary was devoted to compare and analyze those models which are considered to be the most reliable. There were also included ideas of the author regarding the future development of prices. Also, it has been argued, if after all it is still possible to predict future price trends, either based on futures markets, the available media information or econometric models.
|
|
|
The Position of Chile in International Tourism
Beňadiková, Jana ; Valentová, Jana (advisor) ; Dragula, Ladislav (referee)
This diploma thesis analyses the position of Chile in international tourism. The main purpose is to evaluate Chile´s status in international tourism based on the competitiveness of the country. At the begining of the thesis, the theory is defined. Then, the economy and political backgroud of Chile is specified, followed by the description of the preconditions for tourism development and its competitiveness in the tourism industry. Moreover, inbound, outbound and domestic tourism are analysed and followed by tourism impact on the economy of the country. Last chapter predicts future development of international arrivals to the country based on the regression analysis.
|
|
|
Analysis of Economic Indicators Using Statistical Methods
Florek, Michal ; Ing. Svatopluk Hubáček, Ph.D., MBA (referee) ; Novotná, Veronika (advisor)
This thesis is concerned with evaluation of the financial situation of the company using statistical methods to determine the future development of Secondary Vocational School of Protection People and Property ltd. The theoretical part describes economic and statistical concepts, principles, and methods and their use. The practical part analyzes the status quo and calculations of economic indicators using statistical mathods. The results of this analysis serve as a basis for proposals for possible improvements and the establishment of new ecoomic goals of the company.
|
|
| |
|
|
Usage of Public Business Information for Automatic Trading
Gráca, Martin ; Plchot, Oldřich (referee) ; Černocký, Jan (advisor)
In the era of modern technology and high performance computers, the classical trades model getting insufficient. For successful trading, generating stable profit, it is good to use modern technologies and opportunities. The main goal of this work is to develop a trading system based on modern technologies. This work uses public business data from Edgar database managed by U.S. Securities and Exchange Commission (SEC), historical share´s prices and recurrent neural network to create such model. The final system is able to trade successfully and generate profit.
|
|
|
Algorithmic Trading Using Artificial Neural Networks
Červíček, Karel ; Glembek, Ondřej (referee) ; Szőke, Igor (advisor)
Forex is the biggest foreign exchange market. Thanks to high liquidity it is a good candidate for intraday trading with certain trading strategies based on technical and fundamental analysis.Trading strategies can be proposed for automatic algorithmic trading.Strategy in this article is designed with a neural network that holds positions as approximator of time series data based on the exchange rate, which can predict the future.
|
|
|
Bug Prediction Using Data Mining of Test Result History
Matys, Filip ; Vojnar, Tomáš (referee) ; Šimková, Hana (advisor)
Software projects go through a phase of maintenance and, in case of open source projects, through hard development process. Both of these phases are prone to regressions, meaning previously working parts of system do not work anymore. To avoid this behavior, systems are being tested with long test suites, which can be sometimes time consuming. For this reason, prediction models are developed to predict software regressions using historical testing data and code changes, to detect changes that can most likely cause regression and focus testing on such parts of code. But, these predictors rely on static code analysis without deeper semantic understanding of the code. Purpose of this master thesis is to create predictor, that relies not only on static code analysis, but provides decisions based on code semantics as well.
|
|
| |
|
|
Bioinformatics Tool for Prediction of Protein Solubility
Hronský, Patrik ; Burgetová, Ivana (referee) ; Martínek, Tomáš (advisor)
This master's thesis addresses the solubility of recombinant proteins and its prediction. It describes the subject of protein synthesis, as well as the process of recombinant protein creation. Recombinant protein synthesis is of great importance for example to pharmacologic industry. This synthesis is not a simple task and it does not always produce viable proteins. Protein solubility is an important factor, determining the viability of the resulting proteins. It is of course favourable for companies, that take part in recombinant protein synthesis, to focus their effort and their resources on proteins, that will be viable in the end. In this regard, bioinformatics is of great help, as it is capable, with the help of machine learning, of predicting the solubility of proteins, for example based on their sequences. This thesis introduces the reader to the basic principles of machine learning and presents several machine learning methods, used in the field of protein solubility prediction. It deals with the definition of a dataset, which is later used to test selected predictors, as well as to train the ensemble predictor, which is the main focus of this thesis. It also focuses on several specific protein solubility predictors and explains the basic principles upon which they are built, as well as the results of their testing. In the end, it presents the ensemble predictor of protein solubility.
|
|
|
Prediction of Values on a Time Line
Maršová, Eliška ; Bařina, David (referee) ; Zemčík, Pavel (advisor)
This work deals with the prediction of numerical series whose application is suitable for prediction of stock prices. They explain the procedures for analysis and works with price charts. Also explains the methods of machine learning. Knowledge is used to build a program that finds patterns in numerical series for estimation.
|
guest ::
