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The Utilization of Soft Computing in Ordering Cycle Management
Šustrová, Tereza ; Fecenko, Josef (referee) ; Jurová, Marie (referee) ; Marček, Dušan (referee) ; Dostál, Petr (advisor)
This doctoral thesis deals with possibilities of using advanced methods of decision-making - Soft Computing, in company’s ordering cycle management. The main aim of the thesis is to propose an artificial neural network model with an optimal architecture for ordering cycle management within the supply chain management. The proposed model will be employed in an organization involved in retailing to ensure smooth material flow. A design and verification of artificial neural networks model for sales prediction is also part of this doctoral thesis as well as a comparison of results and usability with standard and commonly used statistical methods. Furthermore, the thesis deals with finding a suitable artificial neural network model with architecture capable of solving the lot-size problem according to specified inputs. Methods of statistical data processing, economical modelling and advanced decision-making (Soft Computing) were utilized during the model designing process.
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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.
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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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Deep Learning for Medical Image Analysis
Bíl, Tomáš ; Kodym, Oldřich (referee) ; Španěl, Michal (advisor)
The goal of this thesis is developing convolutional neural network which is able to classify if x-ray images are suitable for cephalometry analysis. Four networks were created and trained on a dataset for this purpose. Two of them are VGG type, one is based on UNet and one is Resnet. The dataset was generated from ct scan images. VGG network with four blocks has got the best results. Measured accuracy performed on test dataset is 97%.
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Emotional State Recognition and Classification Based on Speech Signal Analysis
Černý, Lukáš ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The diploma thesis focuses on classification of emotions. Thesis deals about parameterization of sounds files by suprasegment and segment methods with regard for next used of these methods. Berlin database is used. This database includes many of sounds records with emotions. Parameterization creates files, which are divided to two parts. First part is used for training and second part is used for testing. Point of interest is self-organization network. Thesis includes Matlab´s program which can be used for parameterization of any database. Data are classified by self-organization network after parameterization. Results of hits rates are presented at the end of this diploma thesis.
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Wireless Intrusion Detection System Based on Data Mining
Dvorský, Radovan ; Malinka, Kamil (referee) ; Kačic, Matej (advisor)
Widespread use of wireless networks has made security a serious issue. This thesis proposes misuse based intrusion detection system for wireless networks, which applies artificial neural network to captured frames for purpose of anomalous patterns recognition. To address the problem of high positive alarm rate, this thesis presents a method of applying two artificial neural networks.
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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.
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Algorithmic Trading Using Artificial Neural Networks
Červíček, Karel ; Glembek, Ondřej (referee) ; Szőke, Igor (advisor)
Forex is the biggest foreign exchange market. Thanks to high liquidity it is a good candidate for intraday trading with certain trading strategies based on technical and fundamental analysis.Trading strategies can be proposed for automatic algorithmic trading.Strategy in this article is designed with a neural network that holds positions as approximator of time series data based on the exchange rate, which can predict the future.
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