National Repository of Grey Literature 510 records found  previous11 - 20nextend  jump to record: Search took 0.00 seconds. 
Mobile App with Predictions of e-Sports Matches
Věčorek, David ; Szentandrási, István (referee) ; Herout, Adam (advisor)
E-Sports, also known as progaming (professional gaming) has grown a lot in the last few years. Professional gamers are regularly attending tournaments watched by hundreds of thousands of fans and with prize pools of millions of dollars. There are many video broadcasts of those events and recently betting on e-Sports has also become available. The main goal of this thesis was to create a mobile app for OS Android, which aims to utilize this growth and create a service of providing predictions of results of the e-Sports matches, similar to that existing in regular sports. The application in its current form receives the predictions via Google Cloud Messaging service and shows an Android notification on their arrival. The predictions are then stored on the device into SQLite database so they are available for further view and filtering. After the matches are finished, their results are shown in comparison to the predictions and balance of the predictions is calculated. Users can display information about their subscriptions and predictions under that subscriptions. The app was created in Android Studio IDE with appearance based on the material design guidelines. The app was tested on several devices of different brand and Android version, then it was placed on Google Play for open beta testing. In the future the app will be offered to the users of the service of providing predictions of results of the e-Sports matches.
Prediction of Selected Parameters of Rotational Kinematics Pairs of Machine Tools
Marek, Tomáš ; Šooš, Ĺubomír (referee) ; Kolář, Petr (referee) ; Blecha, Petr (advisor)
The dissertation thesis is used as a methodology for prediction of selected parameters of rotational kinematic pairs of machine tools. The motivation for its writing has been continually increasing requirements for parameters (performance, accuracy, static and dynamic stiffness) of machine tools. The methodology takes into account the availability of suitable measuring devices and description of the design of rotary kinematic pairs. It will be useable for predicting the behavior of rotational kinematic pairs, even at the design stage by applying results to the machine design. The work is processed so that first is used a system approach to suggest methodology for prediction of the behavior of rotary kinematic pair in CNC machine tools, planning measurement strategy and verifying the results, including applications for specific kinematic chain of the selected machine. Based on this system approach and the resulting methodology, the measurement of the rotary kinematic pair was performed. The results of the system approach and measurement are generalized in the form of recommendations for designers of machining centers, allowing to increase the accuracy of the rotational kinematic pair.
Analysis of influence of electromobiles and plug-in hybrids collective employment on distribution network
Přikryl, Ondřej ; Vetiška, Vojtěch (referee) ; Huzlík, Rostislav (advisor)
This work deals with the analysis of influence of electromobiles and plug-in hybrids collective employment into normal operations and its impact on the character of current distribution grid. It contains an analysis and evaluation of these vehicles within the current grid and the smart grid networks, and the calculations of deployment and the influence of electromobiles and plug-in hybrids.
Algorithmic Trading Using Twitter Data
Kříž, Jakub ; Plchot, Oldřich (referee) ; Szőke, Igor (advisor)
This master's thesis describes creation of prediction system. This system predicts future market development based on stock exchange data and twitter messages analysis. Tweets from two different sources are analysed by mood dictionaries or via recurrent neural networks. This analysis results and technical analysis of stock exchange data results are used in multilayer neural network for prediction. A business strategy is created and tested based on results of this prediction. Design and implementation of prediction system is described in this thesis. This system achieved revenue increase more than 25 % of some business strategies by tweets analysis. However this improvement applies for certain data and timeframe.
Prediction of gravity quantities values based on the terrestrial measurements and digital elevation model
Letko, Ivan ; Doudová, Lenka (referee) ; Machotka, Radovan (advisor)
The main objective of this master thesis is random equipartition concentration of measured gravimetric points in the area of interest pursuant by digital terrain model. Remove-Compute-Restore method was used for this purpose. In this thesis normal acceleration of gravity, topographic effect and Faye anomaly were subtracted from measured gravity. The result is Bouguer anomaly with general topographic effect which is interpolated for concentration points. We obtained predicated values of gravity after the restoration of subtracted effects. The main result of the thesis is the map of real gravity and precision evaluation of used method. Furthermore, the reductions of gravity, interpolation methods in programme ArcGIS, Remove-Compute-Restore method and the term of digital terrain model are explained in the thesis.
Assessment of Selected Company Indicators Using Statistical Methods
Rozkydal, Štěpán ; Michalíková, Eva (referee) ; Doubravský, Karel (advisor)
The diploma thesis deals with the assessment of selected financial indicators of the company STAVOČ spol. s r.o. using statistical methods in the years 2013–2020. In the theoretical part, financial indicators, time series analysis, regression analysis and correlation analysis are defined. In the analytical part, the theoretical knowledge is applied to the analysis of selected financial indicators. Some financial indicators are then subjected to statistical analysis on which the prediction of values of indicators for the following two years is carried out or the dependency between the selected indicators is determined. In the last part of the thesis, measures leading to the improvement of the current economic situation of the company are suggested.
Stock Market Prediction via Technical and Psychological Analysis
Petřík, Patrik ; Pospíchal, Petr (referee) ; Rejnuš, Oldřich (advisor)
This work deals with stock market prediction via technical and psychological analysis. We introduce theoretical resources of technical and psychological analysis. We also introduce some methods of artificial intelligence, specially neural networks and genetic algorithms. We design a system for stock market prediction. We implement and test a part of system. In conclusion we discuss results.
Bankruptcy Prediction Modelling in the Agriculture Business
Pokorný, Petr ; Peter,, Markovič, (referee) ; Karas, Michal (advisor)
This master’s thesis is focused on problematic within the prediction of bankruptcy of companies operating in the field of agriculture in Czech republic. First part consists of introduction to companies that do business in field of agriculture and it describes bankruptcy models that are used in academicals sphere. Other part of thesis is divided into two sub-parts. First part is dedicated to an application of data into models of bankruptcy and their evaluation. Second part is focused on improvement of the best model and its main goal is to maximize the precision of the bankruptcy.
The use of artificial intelligence in the capital markets to reduce the risks of trading
Orság, Štěpán ; Budík, Jan (referee) ; Dostál, Petr (advisor)
This thesis deals with the prediction of trading at financial markets and by using the prediction is trying to reduce the risks of entering at the market. The prediction has been work out by using of artificial intelligence. The artificial intelligence is in this thesis represented by neural networks witch model and predict market behavior. The thesis contains a description of the financial markets, exchange trading and its analysis, and artificial intelligence methods. The main part of this thesis is a model for prediction of prices of a particular instrument. This model was developed in MATLAB and should serve as a support for making business decisions. Its aim is to predict the direction and magnitude of movement the price level for the next trading day. The output of this model is processed using the platform MetaTrader 4. At the end are evaluated possible gains from this solution.
Modern coding of speech signals using overcomplete models
Zapletal, Ondřej ; Průša, Zdeněk (referee) ; Rajmic, Pavel (advisor)
The theoretical contents of this thesis are studies of overcomplete models. Those are the models of signals, on which is set for their parametrization more variables, than it's necessary and consequently there's computed so-called sparse solution via iteration algorithms. A goal of this analysis is a selection just of the considerable (sparse) parameters. The theory is based on a linear algebra, vector spaces, bases and so-called frames. The task of the individual project of this thesis is a description and simulation of two speech coders: a classical coder based on linear predictive speech coding and a coder, that's making use of overcomplete stochastic ARMA processes models. A part of their realization is to simulate their decoders and a analyze their reconstruction quality. For their realization there is used MATLAB and an overcomplete models' library (toolbox frames).

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