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Application Monitoring of IoT Devices
Krajč, Patrik ; Ryšavý, Ondřej (referee) ; Matoušek, Petr (advisor)
IoT devices use various standards at the level of the transmission medium and communication protocol. The aim of the work is to create a system, which we can unify a heterogeneous network of the Internet of Things for monitoring purposes. For data collection from the IoT network was used the Home Assistant platform which is uses SNMP agent we created. The monitoring system includes the Nagios core system, which is extended with machine learning-based anomaly detection.
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Application Monitoring of IoT Devices
Krajč, Patrik ; Ryšavý, Ondřej (referee) ; Matoušek, Petr (advisor)
IoT devices use various standards at the level of the transmission medium and communication protocol. The aim of the work is to create a system, which we can unify a heterogeneous network of the Internet of Things for monitoring purposes. For data collection from the IoT network was used the Home Assistant platform which is uses SNMP agent we created. The monitoring system includes the Nagios core system, which is extended with machine learning-based anomaly detection.
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Approximation of Evacuation Curve by the Polynomic Regression Method
Uhlík, Ondřej ; Dobiášová, Lucie ; Kratochvílová, Martina
Prediction of the evacuation process at the time of the emergency is crucial for the subsequent effective coordination of the evacuation and the intervention of the rescue units. Microscopic simulation tools are currently the most advanced method of evacuation modelling, however, their use in the operational phase of construction is inefficient due to the computational time of the simulations and dynamic input data. One of the outputs of the simulations is the evacuation curve. The paper proposes a simplification of the curve by the approximation method of polynomial regression, which demonstrates on basic evacuation scenario. The polynomial coefficients can be used to compile a training set of a machine learning model to predict real-time evacuation curves.
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Varying coefficient models
Sekera, Michal ; Maciak, Matúš (advisor) ; Komárek, Arnošt (referee)
The aim of this thesis is to provide an overview of the varying coefficient mod- els - a class of regression models that allow the coefficients to vary as functions of random variables. This concept is described for independent samples, longi- tudinal data, and time series. Estimation methods include polynomial spline, smoothing spline, and local polynomial methods for models of a linear form and local maximum likelihood method for models of a generalized linear form. The statistical properties focus on the consistency and asymptotical distribution of the estimators. The numerical study compares the finite sample performance of the estimators of coefficient functions. 1
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Estimation of risk-neutral probability density functions from option prices
Krejčí, Kateřina ; Málek, Jiří (advisor) ; Diviš, Martin (referee)
The thesis deals with the estimation of risk-neutral probability density functions from option prices. It focuses on smoothing techniques that are applied to volatility smile. Theoretical part describes the estimation principle and presents some solutions for problems that occur while estimating the risk-neutral distribution. The findings from the theoretical part are used in the practical part and applied to real data. An analysis of the influence of the selection of particular smoothing function on the final distribution is performed. At the end of the thesis a stability test of estimations is performed and the analysis of dynamics of risk neutral distribution is shown on a small data sample.
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Confidence bands for regression curves
Zavřelová, Adéla ; Hlávka, Zdeněk (advisor) ; Maciak, Matúš (referee)
This thesis deals with the constructions of the confidence band for a linear regression model. Basic characteristics of a linear model are given and constructions of different confidence bands are described for models, where the relationship is set by a one variable function. The main focus is on bands of polynomial models.
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Statistical analysis of the consumption of table wine in the Czech Republic with a specific focus on boxed wine
Procházková, Romana ; Šimpach, Ondřej (advisor) ; Jeřábková, Věra (referee)
The aim of this work is a statistical analysis of the consumption of table wine in the Czech Republic with a specific focus on boxed wine. The work is divided into three parts. The first section describes the basic theoretical concepts and statistical methods used in the practical part of this work. The second part analyzes the respondents' answers to survey questions of MML-TGI (Market & Media & Lifestyle -- Target Group Index). The third part is focused on the analysis of time series - the evolution of prices of table wines. The conclusion summarizes the results of this work. Based on the polynomial regression approach the time series of average prices for individual types of table wine are aligned, and they are clearly shown in the graphs.
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