National Repository of Grey Literature 114 records found  previous11 - 20nextend  jump to record: Search took 0.00 seconds. 
Combat Management in Starcraft II Game by Means of Artificial Intelligence
Krajíček, Karel ; Fajčík, Martin (referee) ; Smrž, Pavel (advisor)
This thesis focuses on the use of Artificial Intelligence and design of working module in Real-Time Strategy (RTS) game, StarCraft II.  The proposed solution uses Neural Network and Q-learning for combat management. For implementation, the StarCraft 2 Learning Environment has been used as a means of communication between the designed system and the game. Evaluation of the system is based on its ability to make progress over time.
Fracture Behaviour of Steels and Their Welds for Power Industry
Al Khaddour, Samer ; Kohout, Jan (referee) ; Válka, Libor (referee) ; Dlouhý, Ivo (advisor)
Práce byla zaměřena na ověření platnosti koncepce master křivky pro hodnocení heterogenních svarových spojů, resp. teplotně stárnutých svarů. Současně bylo cílem disertace vyvinout kvantitativní model pro predikci referenční teploty lokalizující tranzitní oblast na teplotní ose za použití dat získaných z tahové zkoušky, a to za použití metody umělých neuronových sítí. Studie je současně zaměřena na heterogenní svarový spoj připravený tavným svařováním. Je zacílena na hodnocení lomového chování v tranzitní oblasti nejméně odolné části svaru, tj. tepelně ovlivněné zóny ferritické oceli v blízkosti zóny natavení s vysokolegovaným materiálem. Pro predikci referenční teploty master křivky je použita zmíněná metoda neuronových sítí, a to za použití dat z tahových zkoušek a měření tvrdosti. Predikovaná referenční teplota byla ověřována na základě výsledku experimentálních měření. Vytvoření modelu za použití neuronových sítí vyžaduje dostatečné množství dat a není vždy snadno tuto podmínku splnit. V případě sledovaného problému to znamenalo použití dat z dostatečně věrohodných zdrojů (skupiny Křehký lom ÚFM AVČR) a se známou metalurgickou historií. Smysl práce je tak možno spatřovat ve vývoji modelu neuronové sítě, která bude dostatečně přesně predikovat referenční teplotu. Celkově byla pro tyto účely použita data z 29 nízkolegovaných ocelí. Pro účely vývoje byly použity kromě hladkých zkušebních tyčí, rovněž tahové zkoušky s obvodovým vrubem testované při kritické teplotě křehkosti (mez makroplastických deformací) a při teplotě pokojové. Při tvorbě modelu byla postupně v různých kombinacích využita všechna data z uvedených zkoušek. Studie ukázala, že referenční teplota charakterizující tranzitní chování lomové houževnatosti oceli s převažující feritickou strukturou je jedinečným parametrem predikovatelným na základě vybraných charakteristik tahových zkoušek.
Neural Networks Classifier Design using Genetic Algorithm
Tomášek, Michal ; Vašíček, Zdeněk (referee) ; Mrázek, Vojtěch (advisor)
The aim of this work is the genetic design of neural networks, which are able to classify within various classification tasks. In order to create these neural networks, algorithm called NeuroEvolution of Augmenting Topologies (also known as NEAT) is used. Also the idea of preprocessing, which is included in implemented result, is proposed. The goal of preprocessing is to reduce the computational requirements for processing of benchmark datasets for classification accuracy. The result of this work is a set of experiments conducted over a data set for cancer cells detection and a database of handwritten digits MNIST. Classifiers generated for the cancer cells exhibits over 99 % accuracy and in experiment MNIST reduces computational requirements more than 10 % with bringing negligible error of size 0.17 %.
Image Compression Based on Artificial Neural Network
Vondráček, Jiří ; Pohl, Jan (referee) ; Jirsík, Václav (advisor)
The thesis is focused on the image compression based on artificial neural network with practical implementation. The objective of this thesis is to explore possibilities of an image compression by artificial neural network and analyze results. In the theoretical part of the work, the fundamentals of artificial neural network are described and basic image compression techniques are explained. In the practical part there is a brief description of the compression program, the comparison of different settings and result evaluation.
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.
Neural network implementation into microcontroler
Čermák, Justin ; Vávra, Jiří (referee) ; Bohrn, Marek (advisor)
This bachelor thesis handles about implementation of multi layer neural networks for character recognition into the PC and microcontrollers. The practical part describes how to design and implement a simple program for pattern recognition of numbers using multi layer neural networks.
Automatic sleep scoring
Schwanzer, Miroslav ; Kozumplík, Jiří (referee) ; Ronzhina, Marina (advisor)
This master thesis deals with classification of sleep stages on the base of polysomnographic signals. On several signals was performed analysis and feature extraxtion in time domain and in frequency domain as well. For feature extraxtion was used EEG, EOG and EMG signals. For classification was selected classification models K-NN, SVM and artifical neural network. Accuracy of classifation is different depending on used method and spleep stages split. The best results achieved classification among stages Wake, REM, and N3, with neural network usage. In this case the succes was 93,1 %.
Application of Neural Networks for Human Face Localization
Žák, Jakub ; Štancl, Vít (referee) ; Švub, Miroslav (advisor)
This paper describes aplication of multi layered neural network for solving problem of detection human face in static picture. This Method has good generalizational capabilities in general and there is no need to assembly complex models of analyzed data. There is also mentioned posibility of using neural network with changed architecture in this work.
Network element project by means of neural network
Pokorný, Petr ; Krček, Petr (referee) ; Šťastný, Jiří (advisor)
The diploma thesis deal with a priority network switch whose model was made in programming environment Matlab - Simulink. Problem of optimal switching is solved by Hopfield’s artificial neural network. Produce of the diploma thesis is a model of packet switch and time-severity comparison of optimalization problem solved with or without artificial neural network. The thesis was developed in research project MSM 0021630529 Intelligent Systems in Automation.
Object Detection in Images
Vaľko, Tomáš ; Motlíček, Petr (referee) ; Švub, Miroslav (advisor)
Object detection in images is quite popular topic for years. What stands for it are a lot of works from this area of computer science. This thesis is about object classification, specifically human faces, which are one of the most interesting objects for processing. For classification we use neural networks, learned on face database. We study what influence has size of face database and preprocessing of digital image on neural network learning. This project implements simple face detector and localizator. It summarizes more and less successful results and indicates possible ways of system development in the future.

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