National Repository of Grey Literature 83 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
Utilization of artificial intelligence in vibrodiagnostics
Dočekalová, Petra ; Huzlík, Rostislav (referee) ; Zuth, Daniel (advisor)
The diploma thesis deals with machine learning, expert systems, fuzzy logic, genetic algorithms, neural networks and chaos theory, which fall into the category of artificial intelligence. The aim of this work is to describe and implement three different classification methods, according to which the data set will be processed. The GNU Octave software environment was chosen for the data application for licensing reasons. Further evaluate the success of data classification, including visualization. Three different classification methods are used for comparison, so that we can compare the processed data with each other.
Overview of Actual Approaches to Classifications
Brezánský, Tomáš ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This bachelor thesis deals with an overview of current approaches to classifications. It describes various approaches to classifications and their algorithms, focuses on neural networks, Bayesian classifiers and decision trees. The main task of this work is to perform experiments with three classification algorithms, namely, the ID3 algorithm, the RCE neural network and the naive Bayesian classifier. The work contains experiments with given algorithms and evaluates the obtained results.
Data Mining with Python
Krestianková, Tamara ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with principles of data mining process, available Python packages for data mining and a demonstration of Python script capable of data analyisis focused on classification techniques. Created classifiers are able to classify subjects into two groups - healthy people and people suffering from Parkinson's disease - based on their biomedical vocal analysis data.
Decision trees
Patera, Jan ; Sáblík, Václav (referee) ; Honzík, Petr (advisor)
This diploma thesis presents description on several algorithms for decision trees induction and software RapidMiner. The first part of the thesis deals with partition and terminology of decision trees. There’re described all algorithms for decision tree construction in RapidMiner. The second part deals with implementation and comparison of chosen algorithms. The application was developed in C++. Based on the real datesets the comparisson of different algorithms was realized using Rapid Miner 4.0.
Detection of modern Slow DoS attacks
Jurek, Michael ; Jonák, Martin (referee) ; Sikora, Marek (advisor)
S rozvojem propojených zařízení v síti internet se počet útoků zvětšuje. Útočníci můžou zneužít takového zranitelného zařízení a vytvořit (D)DoS útok proti své oběti. Tyto útoky se stávají čím dál tím víc sofistikovanější. Proto byla vytvořena nová kategorie DoS útoků s názvem Pomalé DoS útoky, u kterých se útočník snaží napodobit chování standardního uživatele. Útočník se snaží využít všech možností, které mu transportní či aplikační protokol umožňují jako např. náhodné zahazování paketů, neodesílání nebo pozdržování zpráv. Na druhou stranu tvorba vlastních aplikačních výplní těchto protokolů může způsobit stav odepření služby na cíleném aplikačním serveru. Tato práce navrhuje klasifikaci síťových toků a volbu parametrů, které můžou pomoci s detekcí pomalých DoS útoků. Mezi vybranými pomalými DoS útoky jsou Slow Read, Slow Drop a Slow Next. Pro každý útok je popsán proces komunikace z pohledu transportní a aplikační vrstvy. Dále jsou vybrány důležité parametry popisující tyto útoky a v neposlední řadě jsou diskutovány metody a nástroje umožňující tvorbu takových útoků. Tato práce se zabývá možnostmi a nástroji tvorby spojení pro útok a diskutuje základní komunikační koncepty tvorby paralelních spojení. Dále je navržen vlastní generátor pomalých DoS útoků s velkým množstvím parametrů, pomocí nichž může útočník definovat vlastní pomalé DoS útoky. Následující část popisuje testovací prostředí pro testování generovaných útoků, scénáře a nástroje zachycování síťového provozu pro tvorbu vlastního datového souboru, jež je dále použit pro detekci pomalých DoS útoků pomocí metod strojového účení s učitelem. Konrétně jsou použity rozhodovací stromy a náhodné lesy k výběrů důležitých paramterů či sloupců použitelných pro detekci pomalých DoS útoků.
Knowledge Discovery from Databases with Use of the R Language
Krutý, Peter ; Burgetová, Ivana (referee) ; Bartík, Vladimír (advisor)
This thesis is focused on the field of knowledge discovery from databases. Main objective is to research possibilities of R language and its support in this area. Support is researched by experiments using appropriate data sets. More detailed attention is given to the methods of classification, clustering and association rules learning. The output of the thesis is comparison of methods application in R and defining the suitability of using language for knowledge discovery from databases.
Word Sense Disambiguation
Kraus, Michal ; Glembek, Ondřej (referee) ; Smrž, Pavel (advisor)
The master's thesis deals with sense disambiguation of Czech words. Reader is informed about task's history and used algorithms are introduced. There are naive Bayes classifier, AdaBoost classifier, maximum entrophy method and decision trees described in this thesis. Used methods are clearly demonstrated. In the next parts of this thesis are used data also described.  Last part of the thesis describe reached results. There are some ideas to improve the system at the end of the thesis.
Overview of Actual Approaches to Classifications
Brezánský, Tomáš ; Šůstek, Martin (referee) ; Zbořil, František (advisor)
This bachelor thesis deals with an overview of current approaches to classifications. It describes various approaches to classifications and their algorithms, focuses on neural networks, Bayesian classifiers and decision trees. The main task of this work is to perform experiments with three classification algorithms, namely, the ID3 algorithm, the RCE neural network and the naive Bayesian classifier. The work contains experiments with given algorithms and evaluates the obtained results.
Smart Sensor Network with Using Mobile Devices
Tomčík, Milan ; Zbořil, František (referee) ; Samek, Jan (advisor)
This bachelor thesis deals with the use of mobile devices as sensors of various activities. Different types of mobile device sensors are used, in particular the gyroscope, accelerometer and magnetometer. The thesis tackles the possibility of utilization of mobile devices as part of the nodes in a sensor network, while employing mobile device and fusing data obtained from their sensors.
Implementation of Algorithms Based on Decision Trees in C#
Grolig, Lukáš ; Pešek, Martin (referee) ; Stríž, Rostislav (advisor)
This bachelor thesis is focused on selection of data mining algorithms based on decision trees for an analytical system developed under the project System for the Internet security increase based on malware spreading analysis. Selected algorithms are described in greater detais, as well as their implementation in the C# language. These algorithms are then tested with regards to their training speed and classification accuracy. Finally, this thesis presents further conclusions and recommendations  based on performed experiments.

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