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Optimization of rail waste transportation
Ambrozková, Anna ; Hrabec, Dušan (referee) ; Pavlas, Martin (advisor)
The bachelor thesis focuses on optimization of rail waste transportation. Theoretical part is about graph theory and optimization, where is introduced for example representation of graphs, network flows or linear programming. Practical part deals with comparison of road and rail networks, motivational example and at least with the application on real data of whole Czech Republic.
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Traffic assignment optimization models
Holešovský, Jan ; Mrázková, Eva (referee) ; Popela, Pavel (advisor)
Optimalizace toku v síti je klasickou aplikací matematického programování. Tyto modely mají, mimo jiné, široké uplatnění také v logistice, kde se tak snažíme docílit optimálního rozdělení dopravy, např. vzhledem k maximalizaci zisku, či minimalizaci nákladů. Toto pojetí ovšem často problém idealizuje, poněvadž předpokládá existenci jediného rozhodovatele. Takový přístup je možný ve striktně organizovaných sítích jako např. v logistických sítích přepravních společností, železničních sítích či armádním zásobování. Úloha ''Traffic Assignment Problem'' (TAP) se zaměřuje na dopady teorie her na optimalizaci toku, tj. zkoumá vliv více rozhodovatelů na celkové využití sítě. V práci se zaobíráme úlohou TAP s působením náhodných vlivů, k čemuž využíváme metod stochastické a vícestupňové optimalizace. Dále zkoumáme možnosti zlepšení stávajícího využití sítě za rozhodnutí autoritativního rozhodovatele, kterému je umožněn zásah do samotné struktury sítě, k čemuž využíváme víceúrovňové programování.
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Selected optimization models in logistics
Málek, Martin ; Pavlas, Martin (referee) ; Popela, Pavel (advisor)
The bachelor thesis focuses on optimization models in logistics, which are solved by linear programming. Theoretical part introduces basic terms of graph theory, optimization, linear programming and network flows. Practical part contains mathematical models, their implementation, and obtained results. Furthermore, real-world application is solved at the end.
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Stochastic Optimization of Network Flows
Málek, Martin ; Holešovský, Jan (referee) ; Popela, Pavel (advisor)
Magisterská práce se zabývá stochastickou optimalizací síťových úloh. Teoretická část pokrývá tři témata - teorii grafů, optimalizaci a progressive hedging algoritmus. V rámci optimalizace je hlavní část věnována stochastickému programování a dvoustupňovému programování. Progressing hedging algoritmus zahrnuje také metodu přiřazování scénářů a modifikaci obecného algoritmu na dvou stupňové úlohy. Praktická část je věnována modelům na reálných datech z oblasti svozu odpadu v rámci České republiky. Data poskytl Ústav procesního inženýrství.
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Analysis of Captured DNS Traffic
Hmeľár, Jozef ; Kekely, Lukáš (referee) ; Kováčik, Michal (advisor)
This thesis is focused on the analysis of captured DNS traffic. Introduction of this thesis is focused of basic desciption of computer networks , DNS and description of network flows. Then, the work focused on analysis Netflow format, IPFIX and PCAP, the analysis and implementation of tool for analyzing DNS traffic in C++ programming language. The conclusion is devoted to the results of the implemented tools.
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Models for network flow identification
Smejkalová, Veronika ; Kůdela, Jakub (referee) ; Pavlas, Martin (advisor)
The bachelor thesis is focused on development of a mathematical model of network flow in waste managment. The theoretical part of thesis deals with graph theory, network flow and optimization. The next chapter introduces the mathematical model. The model was compiled with the use of Information systems of waste management. The data are very often burdened by error. The task of the model is revelation of those errors to make the data useful. This thesis also includes suggestions for further development.
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Distributed Tool for Extraction of Information from Network Flows
Sedlák, Michal ; Grégr, Matěj (referee) ; Žádník, Martin (advisor)
This work deals with the extraction of information from flow records that are the result of network monitoring by the IPFIX system. The goal of the work is to design a tool that allows querying stored network flows created by the open-source collector IPFIXcol2. Querying is performed with the highest possible efficiency and performance in mind, which is achieved by using appropriate data structures and thread-level parallelization, as well as by using multiple machines.
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Detection of Malware Communication in Network Flows
Korvas, Václav ; Matoušek, Petr (referee) ; Ryšavý, Ondřej (advisor)
This thesis deals with the issue of network communication of malicious code, methods of their analysis and especially the comparison of accuracy of different machine learning algorithms among themselves. The paper presents a comparison of the accuracy of different machine learning algorithms, both on test data and when used in real life. Accuracy, F1-score and false positive rate were used as metrics to evaluate the results. On the test data, the Random Forest and XGBoost algorithms were found to be the most accurate, achieving 99.2% accuracy with a rate of false positivity of 0.6%. In real-life experiments, approximately 9% of flows were incorrectly detected and classified as malware. When the computer was compromised, the rate of flows classified as malware increased to 18%, and several indicators of compromise were captured and confirmed the infection of the computer.
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Optimization in transportation problems
Brandstetter, Matyáš ; Mrázková, Eva (referee) ; Popela, Pavel (advisor)
The thesis deals with optimization models in transportation problems. It begins with a brief introduction to graph theory, linear programming and network flows. The text is accompanied with pictures made in GeoGebra. The presented problems are explained with particular examples. Transportation problems in network flows and their Python implementation recieve more attention in throughout the thesis. Functions written in Python help with data preprocessing and preparation, that is needed in order to solve larger optimization problems.
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Selected Advanced Stochastic Programming Models
Brzobohatý, Jan ; Hrabec, Dušan (referee) ; Popela, Pavel (advisor)
This diploma thesis deals with stochastic dominance. The goal is to lay the foundations for defining stochastic dominance, to describe its properties and to explain this concept on simple examples. Another goal is to apply this concept to network problems with random price. Examples in this thesis also contain solutions and python code how to find them.
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