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Prediction of Multiple Time Series at Stock Market Trading
Palček, Peter ; Zbořil, František (referee) ; Rozman, Jaroslav (advisor)
The diploma thesis comprises of a general approach used to predict the time series, their categorization, basic characteristics and basic statistical methods for their prediction. Neural networks are also mentioned and their categorization with regards to the suitability for prediction of time series. A program for the prediction of the progress of multiple time series in stock market is designed and implemented, and it's based on a model of flexible neuron tree, whose structure is optimized using immune programming and parameters using a modified version of simulated annealing or particle swarm optimization. Firstly, the program is tested on its ability to predict simple time series and then on its ability to predict multiple time series.
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Water Management Analysis of Storage Capacity of the Vranov Reservoir
Vítková, Lucie ; Havlík, Martin (referee) ; Marton, Daniel (advisor)
The current persistent drought and changes in the climate system have raised water managers expert questions about how to manage water resources in the future. The manifestation of climate change in hydrological series and their influence on the magnitude of threats to the storage functions of reservoirs are more often investigated. Already today, long-term shortages of storage capacity in reservoirs lead to the introduction of special manipulations on water structures. The aim of the thesis is to perform the analysis of time series, respectively decomposition of hydrological series average annual and monthly discharges. Create extended hydrological bases using synthetic discharge series generators and develop a comprehensive analysis of storage volume without considering losses even with the introduction of losses from the water surface vapor in the UNCE RESERVOIR program. The created discharge series are compared and evaluated on the basis of statistical characteristics and reservoir storages results with the real discharge series. The practical app is conducted on the Vranov reservoir in the Dyje River Basin.
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Gathering and processing of access point data
Kislinger, Jan ; Szőcs, Juraj (referee) ; Růčka, Lukáš (advisor)
This work deals with gathering and processing of access point data. At the beginning, we introduce the SNMP protocol and MIB databases. Additionally, there is ways to gather data. The next section describes data processing. First, using moving averages and candelstick chart, then calculate the predicted values. Finally, it describes a program that gather data and draws them into the charts.
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Pattern Finding in Dymanical Data
Budík, Jan ; Hynčica, Ondřej (referee) ; Honzík, Petr (advisor)
First chapter is about basic information pattern learning. Second chapter is about solutions of pattern recognition and about using artificial inteligence and there are basic informations about statistics and theory of chaos. Third chapter is focused on time series, types of time series and preprocessing. There are informations about time series in financial sector. Fourth charter discuss about pattern recognition problems and about prediction. Last charter is about software, which I did and there are informations about part sof program.
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Selected methods of time series analysis with STATISTICA
Indrová, Magdalena ; Hudecová, Šárka (advisor) ; Zichová, Jitka (referee)
This work deals with the use of STATISTICA software for the basic analysis of time series. The thesis is focused on time series decomposition, mainly on the trend elimination. First, the basic methods of the analysis are described theoretically, namely, trend modeling using mathematical curves (polynomial, exponential, logistic and Gompertz) and adaptive approach (moving averages, simple exponential smoothing and Holt's method). These methods are then applied to three selected data sets (unnamed bank's balance sheet from 1998 to 1993, ship construction trends between 1820 and 1997, and CZK/EUR Exchange rate from 1998 to 2012). All analytical procedures are described in detail and individual program outputs are thoroughly explained and commented.
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Water Management Analysis of Storage Capacity of the Vranov Reservoir
Vítková, Lucie ; Havlík, Martin (referee) ; Marton, Daniel (advisor)
The current persistent drought and changes in the climate system have raised water managers expert questions about how to manage water resources in the future. The manifestation of climate change in hydrological series and their influence on the magnitude of threats to the storage functions of reservoirs are more often investigated. Already today, long-term shortages of storage capacity in reservoirs lead to the introduction of special manipulations on water structures. The aim of the thesis is to perform the analysis of time series, respectively decomposition of hydrological series average annual and monthly discharges. Create extended hydrological bases using synthetic discharge series generators and develop a comprehensive analysis of storage volume without considering losses even with the introduction of losses from the water surface vapor in the UNCE RESERVOIR program. The created discharge series are compared and evaluated on the basis of statistical characteristics and reservoir storages results with the real discharge series. The practical app is conducted on the Vranov reservoir in the Dyje River Basin.
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Hydrological Time Series Analysis for Chosen Sub Catchment in Morava River Basin
Černý, Vojtěch ; Benáčková, Kateřina (referee) ; Marton, Daniel (advisor)
Current climate conditions raise questions about how climate change should affect the hydrological regime of the Czech Republic. The main questions are: I) Is climate change serious and is it already tangible in hydrological series? II) Are there significant changes in the climatic conditions, or in the flow of the river network? III) How does climate change affect hydrological conditions in the catchment? IV) Are there non-stationary tendencies in the hydrological series caused by climate change? The aim of this work was to perform a basic analysis of hydrological time series and estimated its possible changes. The analysis was done with using autocorrelation function, spectral density, moving averages methods, statistical characteristics, empirical line of probability of exceeding and last but not least by decomposing the time series. The practical application was applied on time series of average monthly flows determined in the hydrometric profile of Dalečín in the Svratka river basin.
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Selected methods of time series analysis with STATISTICA
Indrová, Magdalena ; Hudecová, Šárka (advisor) ; Zichová, Jitka (referee)
This work deals with the use of STATISTICA software for the basic analysis of time series. The thesis is focused on time series decomposition, mainly on the trend elimination. First, the basic methods of the analysis are described theoretically, namely, trend modeling using mathematical curves (polynomial, exponential, logistic and Gompertz) and adaptive approach (moving averages, simple exponential smoothing and Holt's method). These methods are then applied to three selected data sets (unnamed bank's balance sheet from 1998 to 1993, ship construction trends between 1820 and 1997, and CZK/EUR Exchange rate from 1998 to 2012). All analytical procedures are described in detail and individual program outputs are thoroughly explained and commented.
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Využití predikčních modelů v analýze nezaměstnanosti
Stejskalová, Kateřina
The purpose of this diploma thesis is compare selected prediction models. These models are used for analysis of the South Moravian Region unemployment and then compared with unemployment development in the Czech Republic. This thesis is separated to two parts: theoretical and practical. The theoretical part is used to describe selected prediction models, psychological effects of unemployment on human being and impact of unemployment on the society. The second part is focused on the analysis of the South Moravian Region. Prediction models such as trend lines, moving averages, ARIMA method and neural network are used and compared which each other. All predictions are based on data from the Czech Statistical Office and covers period between year 1993 and 2012. This data is measured with periodicity of three months.
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