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Genetic Programming in Prediction Tasks
Machač, Michal ; Mrázek, Vojtěch (referee) ; Sekanina, Lukáš (advisor)
This thesis introduces various machine learning algorithms which can be used in prediction tasks based on regression. Tree genetic programming and linear genetic programming are explained more thoroughly. Selected machine learning algorithms (linear regression, random forest, multilayer perceptron and tree genetic programming) are compared on publicly available datasets with the use of scikit-learn and gplearn libraries. A core part of this project is a new implementation of linear genetic programming which was developed in C++, tested on common symbolic regression problems and then evaluated on real datasets. Results obtained with the proposed system are compared with the results obtained with gplearn.
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Determination of the performance of the cooling circuit - cooling tower
Velešík, Aleš ; Hanzal, Luděk (referee) ; Baláš, Marek (advisor)
The aim of this work is to determine the performance and description of the cooling circle in the cooling tower. In order to do that there was applied the linear regression approach in order to create structural empirical model of the cooling tower. The data obtained was analysed through QC expert software, which, if correct data applied, identifies suitable model for specific tower. The models created will be used for diagnostics of the cooling circles and as a comparison tool with other cooling towers in the future. Thus, the findings of this thesis are polynoms, which in thic technological setup characterise the models of the cooling towers.
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Evolutionary Design of Simulator Based on Cellular Automata
Brigant, Vladimír ; Šperka, Svatopluk (referee) ; Mrnuštík, Michal (advisor)
This work describes concept of a cellular automata (CA) simulator, which is able to predict behaviour of a complex spatial system. This prediction is based on available training data and transition rule acquired from regression analysis powered by evolutionary algorithms. Two regression analysis methods (linear and logistic regression) are suggested, implemented and compared on urban growth prediction of Brno city.
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Home Information System
Knyrevich, Michail ; Matějka, Pavel (referee) ; Szőke, Igor (advisor)
This bachelor's thesis involves the development of the Informational system for home, especially its Energy module. Some existing informational systems of this topic are analyzed there. Further, there is a formal concept of self Energy module , which is based on gained information. The part of this concept is prediction system of energetic expenses, which uses a weather monitoring. Realization and testing with usage of web technologies (especially the Zend Framework) are placed at the end of my thesis.
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Computer Identification Based on Packet's Timestamps
Krba, Martin ; Košař, Vlastimil (referee) ; Kaštil, Jan (advisor)
Basic way how to identify a device in computer network is by MAC address and IP address. Main goal of this work is to create an application capable of clear identification of devices in computer network regardless change of their MAC address or IP address. This is done by exploiting tiny deviations in hardware clock known as clock skew. They appear in every clock based on quartz oscillator. Using clock skew is beneficial, because there is no need of any changes in fingerprinted device nor their cooperation. Accessing these values is done by capturing packets with timestamps included. Application of this method is very wide, for example computer forensics, tracking the device using different access points or counting devices behind router with NAT.
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