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Methods for Classification of WWW Pages
Svoboda, Pavel ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
The main goal of this master's thesis was to study the main principles of classification methods. Basic principles of knowledge discovery process, data mining and using an external class CSSBox are described. Special attantion was paid to implementation of a ,,k-nearest neighbors`` classification method. The first objective of this work was to create training and testing data described by 'n' attributes. The second objective was to perform experimental analysis to determine a good value for 'k', the number of neighbors.
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Adaptive Model for Simulation of Atmospheric Pollution
Pazúriková, Jana ; Šátek, Václav (referee) ; Dvořák, Radim (advisor)
Air pollution harms the environment and human welfare. Computer models and their simulation are useful tools for deeper understanding of processes behind as they quite accurately represent the dispersion and transformation of pollutants with advection diffusion equation or by other concepts. Current models give valid results only to constrained cases of initial conditions. The general model combining the several specific models which is able to change according to input parametres and improve with training is proposed. The adaptiveness of the system is provided by decision tree as data structure with information for selection and combination process and genetic algorithm as optimization method for adjusting the tree. The evaluation of implemented system proves that the combination of models gives better results than models themselves. Even with simple specific models, the system has achieved results comparable to state-of-art models of air pollution.
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Creation of Unit for Datamining
Krásenský, David ; Burgetová, Ivana (referee) ; Lukáš, Roman (advisor)
The goal of this work is to create data mining module for information system Belinda. Data from database of clients will be analyzed using SAS Enterprise Miner. Results acquired using several data mining methods will be compared. During the second phase selected data mining method will be implemented such as module of information system Belinda. The final part of this work is evaluation of acquired results and possibility of using this module.
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Identification of Application Protocols
Wrona, Jan ; Bartoš, Václav (referee) ; Kořenek, Jan (advisor)
This thesis is focused on identification of application protocols with emphasizing the speed of their recognition and following possibility of hardware implementation. Nowadays tools are not suitable for fast identification of application protocols in current network monitoring devices, because the decision is not provided for the first packets of network flow. Therefore this thesis propose new model for fast and reliable identification of application protocols. The model was implemented and tested on HTTP, SIP, SMTP and DNS protocols and results were compared to regular expressions and nDPI and libprotoident libraries. For all these protocols, the proposed model has comparable accuracy to other methods, but also provides fast result based on the first packets of the flow.
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Artificial Intelligence in Bang! Game
Kolář, Vít ; Lodrová, Dana (referee) ; Orság, Filip (advisor)
The goal of this master's thesis is to create an artificial intelligence for the Bang! game. There is a full description of the Bang! game, it's entire rules, player's using strategy principles and game analysis from UI point of view included. The thesis also resumes methods of the artificial intelligence and summarizes basic information about the domain of game theory. Next part describes way of the implementation in C++ language and it's proceeding with use of Bayes classification and decision trees based on expert systems. Last part represent analysis of altogether positive results and the conclusion with possible further extensions.
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ANALYSIS AND DEFINITION OF DECISION PROBLEMS OF EXPERT IN REAL ESTATE VALUATION
Krejza, Zdeněk ; Bradáč, Albert (referee) ; Abraham, Karel (referee) ; Tichá, Alena (advisor)
The thesis deals with the decision-making of the expert in real estate valuation. Due to the complexity of the process and the difficulties of valuation it can be assumed that the decision will be an arduous process. It is obvious that the choice of an expert is crucial to the result of the valuation process. This topic is currently relatively little explored, and therefore the work will deal with the analysis and formulation of decision problems expert in real estate valuation. The thesis analyses the current status of forensic engineering and decision-making regarding to real estate valuation. The general decision-making process, divided into seven steps, is adapted to the requirements of expert decision-making in real estate valuation. As in the managerial decision-making process, property valuation is also divided into three levels. These three levels considered the described fundamental decision problems that lead to the formulation of the expert decision-making principles in real estate valuation. For better understanding the extensiveness of the decision-making process in the valuation of real estate the author created a decision tree respectively schemes whose functionality has been verified at the end of the thesis, exemplified with the help of a specific case study of the determined price in real estate valuation.
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The idnetification of the objects in the imege
Zavalina, Viktoriia ; Fliegel, Karel (referee) ; Boleček, Libor (advisor)
Master´s thesis deals with methods of objects detection in the image. It contains theoretical, practical and experimental parts. Theoretical part describes image representation, the preprocessing image methods, and methods of detection and identification of objects. The practical part contains a description of the created programs and algorithms which were used in the programs. Application was created in MATLAB. The application offers intuitive graphical user interface and three different methods for the detection and identification of objects in an image. The experimental part contains a test results for an implemented program.
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Design of exercises for data mining - Classification and prediction
Martiník, Jan ; Malý, Jan (referee) ; Burget, Radim (advisor)
My master's thesis on the topic of "Design of exercises for data mining - Classification and prediction" deals with the most frequently used methods classification and prediction. There are association rules, Bayesian classification, genetic algorithms, the nearest method neighbor, neural network and decision trees on the classification. There are linear and non-linear prediction on the prediction. This work also contains a summary of detail the issue of decision trees and a detailed algorithm for creating the decision tree, including development of individual diagrams. The proposed algorithm for creating the decision tree is tested through two tests of data dowloaded from Internet. The results are mutually compared and described differences between the two implementations. The work is written in a way that would provide the reader with a notion of the individual methods and techniques for data mining, their advantages, disadvantages and some of the issues that directly relate to this topic.
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