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Water cooling intensity prediction for given thickness of oxide layer
Haluza, Vít ; Hrabovský, Jozef (referee) ; Pohanka, Michal (advisor)
This diploma thesis is dealing with the impact of oxide scales on heat conduction. One of the main tools that were used are numerical simulations. Heat conduction is modelled by solving partial differential equations. Regression models and artificial neural networks are used for the prediction of the influence of oxides on cooling intensity. Determination of the conditions when the cooling was intensified and comparison of individual methods of prediction are the main results of the thesis.
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Data Mining in Small Business
Sabovčik, František ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
Tato práce si klade za cíl vyhodnotit techniky získávání znalostí pro využití v prostředí malého podnikání. Po prozkoumání dat a konzultace s doménovymi experty byly vybrány dvě úlohy: analyza nákupního košíku a predikce prodejů. Pro analyzu nákupního košíku byl využit algoritmus Relim pro vyhledávání častych itemsetů a metriky určující zajímavost asociačních pravidel. Pro úlohu predikce prodejů byl implementován dekompoziční model, SARIMA, MARS a neuronové sítě s časovym oknem. Modely byly vyhodnoceny. Pomocí optimalizace hyper-parametrů bylo dosaženo přijatelnych vysledků. Oproti předpokladům nedošlo při dodání dat o počasí a využití nelineárních modelů ke zlepšení oproti SARIMA. Predikce byla implementována jako služba na straně serveru pro testování v produkčním prostředí.
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Analysis of Economic Indicators Using Statistical Methods
Wahed, Sam ; Doubravský, Karel (referee) ; Novotná, Veronika (advisor)
The Bachelor’s Thesis analyses through statistical and demographic methods the structure of the population of Czech Republic in a past representation and future projection, in relation to its workforce. The methods of processing the time series and the demographic relations are presented in the theoretical part and these methods are further elaborated in the practical part. The results of the Bachelor’s Thesis that have been discovered by the analysis are assessed in the Conclusion that also contains a proposition of a solution as a contribution to the situation ascertained. The Attachment of the Bachelor’s thesis is a statistical calculator programmed in VBA to facilitate the calculations.
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Identification of tire model parameters
Olišar, Petr ; Zháňal, Lubor (referee) ; Porteš, Petr (advisor)
The main goal of this thesis is to obtain lateral parameters of the Magic Formula tire model of a tire commonly used in Formula Student competition. Both the author and the supervisor of the thesis know the tire name and its specification, but the research company that did the tire testing and provided me with the date prohibits sharing this of data publicly, so the tire designation is not mentioned in this thesis. The first chapter covers main theoretical facts related to a tire, briefly describes some of the tire models and shows possibilities how to determine tire characteristics that are used in a tire model. The thesis describes how to process raw tire data measured during a laboratory experiment using scripts created in Matlab software. The inputs variables are slip angle, lateral force, normal force and inclination angle. Raw data are splitted into parts, main coefficients of the Magic formula model (B, C, D, E, Sh, Sv) are calculated and subsequently the lateral parameters are obtained using least square method to fit parameters into the measured data. The works gives two main outcomes. The first output is a set of Matlab scripts that can be used to determine lateral parameters of any tire that has the same input data format as presented. A TIR file of the Formula Student tire in case of lateral slip is the second result of the work. This can be used for vehicle dynamics simulation of Formula Student racing car. The thesis also offers a comparison between parameters, which I calculated, and those gained thanks to Optimum Tire software by Calspan research company. Additionally the work shows the effect of load and inclination angle on lateral force.
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Multi-Agent System for the Prediction of the Effect of Mutations on Protein Stability
Doseděl, Ondřej ; Martínek, Tomáš (referee) ; Musil, Miloš (advisor)
Proteiny jsou základním stavebním blokem všech žijících organismů, kde jsou zodpovědné za mnoho důležitých procesů. Jsou složeny z řetězců aminokyselin. Tyto řetězce mohou být jakkoliv změněné. Tomuto procesu se říká mutace a může být samovolná nebo indukovaná v laboratoři. Cílem této práce bylo vytvoření nových modelů pro určení stability proteinů. Skládá se ze dvou modelů. První model je multi-agentní systém pro klasifikaci stability proteinů. Nejlepší multi-agentní systém získal přesnost 0.7 a 0.41 MCC. Druhá část se~zabývala predikcí konkrétních hodnot G, kde byl vytvořený Extreme Gradient Boosting model, který získal 1.67 RMSE a 0.53 PCC. Součástí této práce byly představené 2 datasety, které jsou na sobě plně nezávislé, použitelné pro trénování a validaci modelů.
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Interactive software tools for teaching signal processing
Pacas, Ondrej ; Rajmic, Pavel (referee) ; Mangová, Marie (advisor)
This thesis deals with creation of four interactive applications for educational purposes in the field of digital signal processing. The goal of this work is to create four applications which will visually interpretate each of the methods of signal processing. This involves applications for linear regression and least squares method, interpolation and signal reconstruction from its samples, discrete linear convolution and discrete cross-correlation. Applications are created using JavaScript programming language.
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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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Assessment of the strength of concrete structures by a combination of non-destructive and destructive methods
Masařík, Dominik ; Kocáb, Dalibor (referee) ; Cikrle, Petr (advisor)
This bachelor's thesis is about a combination of destructive and non-destructive methods, including a description of the most modern devices of reflection hardness testers. Further on, an analysis of the new norm ČSN EN 13791 is performed. The practical part of the thesis is about measuring on concrete bodies using the latest rebound hardness tester SilverSchmidt, ultrasonic pulse method and tests of compressive strenght of concrete on individual bodies. The evaluation took place on the base of established linear and quadratic regressions on the test specimens. In situ compressive strength was deternibed according to the procedures specified in the ČSN EN 13791 standard.
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