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Creation of New Prediction Units in Data Mining System on NetBeans Platform
Havlíček, David ; Bartík, Vladimír (referee) ; Lukáš, Roman (advisor)
The issue of this master's thesis is a creation of new prediction unit for existing system of knowledge discovery in database. The first part of project deal with general problems of knowledge discovery in database and predictive analysis. The second part of the project deal with system developed on FIT, for which is module implemented, used technologies, concept and implementation of mining module for this system. The solution is implemented in Java language and is a built on the NetBeans platform.
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Condition monitoring of engine block machining - Plasma
Váško, Ondřej ; Krejčí, Jakub (referee) ; Pikula, Stanislav (advisor)
The aim of this thesis is to design and implement two methods of predictive analysis for company Škoda Auto a.s. In the first part I have conducted a literature search on methods of predictive diagnostics. In the next part, with help from thesis consultant in Škoda Auto a.s., the analysis of the assembly line and data blocks from machinery and measuring has been made. Then I designed and programmed data generator based on real data. I created two methods of predictive diagnostics, capable of analyzing input data and deciding about their condition. In the end I tested these two methods and evaluated accuracy of their prediction. Main output of my thesis is two methods of predictive diagnostics, feasible in real world.
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Echo state neural network for stock market prediction
Pospíchal, Ondřej ; Mašek, Jan (referee) ; Burget, Radim (advisor)
This thesis deals with an echo state network and with acceleration of its learning by implementing the echo state network on a graphics processor. The theoretical part consists of the description of neural networks and some selected types of neural networks, on which is based the echo state network. After that, there are some other algorithms described used for time series analysis and last but not least, the tools that were used in the practical part of the thesis were briefly described. The practical part describes the creation of the accelerated version of the echo state network. After that, there is described the creation of input data sets of real financial indexes, on which the echo state network and the other algorithmns were then tested. By analyzing this accelerated version it was found that its learning speed did not reach the theoretical expectations. The accelerated version works slower, but with greater precision. By analyzing the results of the measurement of the other algorithmns it was found that the highest precision is achieved by solutions based on the neural network principle.
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Assessing Economic Situation of a Company and Proposals for Its Improvement
Vitula, Miroslav ; Michalíková, Eva (referee) ; Doubravský, Karel (advisor)
This Master’s Thesis deals with the financial analysis and assessment of the economic situation of Pears Health Cyber s. r. o. with proposals for its improvement. The theoretical part of the thesis is devoted to economic and statistical theory. It describes financial ratios, financial analysis tools, time series, regression and correlation analysis. The analytical part applies selected statistical and financial methods to evaluate the financial situation of the company and evaluates predictions for future years based on the calculated regression models. On the basis of the financial and statistical analysis, suggestions for improving the company's financial situation are developed.
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Condition monitoring of engine block machining - Plasma
Váško, Ondřej ; Krejčí, Jakub (referee) ; Pikula, Stanislav (advisor)
The aim of this thesis is to design and implement two methods of predictive analysis for company Škoda Auto a.s. In the first part I have conducted a literature search on methods of predictive diagnostics. In the next part, with help from thesis consultant in Škoda Auto a.s., the analysis of the assembly line and data blocks from machinery and measuring has been made. Then I designed and programmed data generator based on real data. I created two methods of predictive diagnostics, capable of analyzing input data and deciding about their condition. In the end I tested these two methods and evaluated accuracy of their prediction. Main output of my thesis is two methods of predictive diagnostics, feasible in real world.
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Echo state neural network for stock market prediction
Pospíchal, Ondřej ; Mašek, Jan (referee) ; Burget, Radim (advisor)
This thesis deals with an echo state network and with acceleration of its learning by implementing the echo state network on a graphics processor. The theoretical part consists of the description of neural networks and some selected types of neural networks, on which is based the echo state network. After that, there are some other algorithms described used for time series analysis and last but not least, the tools that were used in the practical part of the thesis were briefly described. The practical part describes the creation of the accelerated version of the echo state network. After that, there is described the creation of input data sets of real financial indexes, on which the echo state network and the other algorithmns were then tested. By analyzing this accelerated version it was found that its learning speed did not reach the theoretical expectations. The accelerated version works slower, but with greater precision. By analyzing the results of the measurement of the other algorithmns it was found that the highest precision is achieved by solutions based on the neural network principle.
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Creation of New Prediction Units in Data Mining System on NetBeans Platform
Havlíček, David ; Bartík, Vladimír (referee) ; Lukáš, Roman (advisor)
The issue of this master's thesis is a creation of new prediction unit for existing system of knowledge discovery in database. The first part of project deal with general problems of knowledge discovery in database and predictive analysis. The second part of the project deal with system developed on FIT, for which is module implemented, used technologies, concept and implementation of mining module for this system. The solution is implemented in Java language and is a built on the NetBeans platform.
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Use of VBA in business practice
Nagrant, Richard ; Benáčanová, Helena (advisor) ; Fortinová, Jana (referee)
My diploma thesis is dedicated to the issue of data mining, its part of predictive analysis and then process that is used in HP for different prediction. The introductory part describes the concept of data mining, its role and benefits. To one of its tasks fall predictive analysis, where I discussed the principles of its use. Then follows framework HP, which uses one of the tasks of predictive analysis. In the practical part, I applied the use VBA to automate one part of the process of converting text to numerical data, assuming different rules. The result is a set of macros support, system sheet and the new ribbon for data transformation.
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