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The Study of Inventory Management in Connection with Manufacturing Process
Tieber, Michael ; Klíma, Jan (referee) ; Jurová, Marie (advisor)
This master’s thesis deals with problems of inventory management in the International Repair Centre for Symbol Technologies Czech Republic s.r.o.. Actual inventory management is described with a focus on materials planning, storage and evidence of inventory movements using information database systems. A part of the thesis is also an analysis of inventory categories from several different aspects. The purpose of the master’s thesis is to submit suitable suggestions of how to improve existing inventory management processes.
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Stochastic management storage function of water reservoir using method of artificial intelligence
Kozel, Tomáš ; Fošumpaur, Pavel (referee) ; Zezulák,, Jiří (referee) ; Starý, Miloš (advisor)
The main advantage of stochastic forecasting is fan of possible value, which deterministic method of forecasting could not give us. Future development of random process is described better by stochastic then deterministic forecasting. We can categorize discharge in measurement profile as random process. Stochastic management is worked with dispersion of controlling discharge value. In thesis is described construction and evaluation of adaptive stochastic model base on fuzzy logic, neural networks and evolution algorithm, which are used stochastic forecast from forecasting models described in thesis. The learning fuzzy model and neural network is used as replacement of classic optimization algorithm (evolution algorithm). Model was tested and validated on made up large open water reservoir. Results were evaluated and were compared with model base on traditional algorithms, which was used for 100% forecast (forecasted values are real values). The management of the large open water reservoir with storage function, which was given by stochastic adaptive managing, was logical. The main advantage of fuzzy model and neural network model is computing speed. Classical optimization model is needed much more time for same calculation as fuzzy and neural network model, therefore classic model used clusters for stochastic calculation.
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Decision making based on partially known decision trees
Poláček, Tomáš ; Dostál, Petr (referee) ; Koutský, Jaroslav (referee) ; Váchal, Jan (referee) ; Dohnal, Mirko (advisor)
There is a wide range of different algorithms for insolvency prediction. The complex concept of insolvency proceedings from the point of view of both parties (debtor versus creditor) and from the point of view of the macroeconomics in this dissertation is new. It is often very difficult to generate forecasts using numerical quantifiers and traditional statistical methods. The reason is the lack of input data. Therefore, the work uses trend analysis tools based on the least information intensive quantifiers, ie trends, increasing, constant, and decreasing. A trend model solution is a set of scenarios where a set of variables is quantified by these trends. All possible transitions between the scenarios are generated and plotted in transition graphs. The oriented transition graph has as a node a set of scenarios, and as a branch the transitions between the scenarios. The given path through the transition graph describes any possible future and past behavior of the insolvency system being investigated. The Transition graph is a complete list of trend-based forecasts. The heuristics for determination of the payoff values from the insolvency proceedings applicable to the decision tree tools and the generated transition graphs from trend analyzes are also presented and used in the thesis. A nine-dimensional model serves as a case study. Vague variables are used in models that may have a major impact on the entire insolvency process, eg greed level and political situation.
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The Use of Artificial Intelligence on Commodity Markets
Volf, Petr ; Geroč, Ján (referee) ; Dostál, Petr (advisor)
Tato diplomová práce se zabývá problematikou obchodování na komoditních trzích. Řešení problematiky spočívá ve využití umělé inteligence, konkrétně neuronových sítí, k technické analýze vývoje ceny vybrané komodity a snaze o co nejpřesnější predikci budoucího vývoje ceny pro podporu investičního rozhodování. Model neuronové sítě je vytvořen a použit pro predikci v programu MATLAB.
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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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Educational video codec
Dvořák, Martin ; Hála, Ondřej (referee) ; Slanina, Martin (advisor)
The first goal of diploma thesis is to study the basic principles of video signal compression. Introduction to techniques used to reduce irrelevancy and redundancy in the video signal. The second goal is, on the basis of information about compression tools, implement the individual compression tools in the programming environment of Matlab and assemble simple model of the video codec. Diploma thesis contains a description of the three basic blocks, namely - interframe coding, intraframe coding and coding with variable length word - according the standard MPEG-2.
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Wind shear as a dangerous fenomenon in aviation
Novozámský, Adam ; Jebáček, Ivo (referee) ; Krška, Karel (advisor)
This thesis is about wind shear and its influence on aviation. There is wide theoretical description of wind shear and it’s implemented into aviation practice. There are also methods of observation, forecasting and reporting, for both pilots and meteorologist described. In this thesis, pilots can find useful recommendations for dealing with wind shear during the flight. Every reader can also read about famous aviation accidents and look at models of weather that caused those accidents. At the end of thesis there are analyses of a rawiosonde measurements related to wind shear reports. This whole thesis is focused on increasing awareness of wind shear in aviation from angle of view of both pilots and aviation meteorologist.
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Faktory ovlivňující objem bytové výstavby v České republice
Tesařová, Veronika
The diploma thesis aims to identify the factors affecting the level of housing construction in the Czech Republic and to build an econometric model. The first part provides an overview of the literature. The chapter Methodology describes the methods used to build an econometric model and describes the different characteristics that determine the level of housing construction. Their influence is validated using multivariate regression analysis in chapter Results, where there is also a forecast level of housing construction for 2015. At the end of this thesis the results are interpreted.
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