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Thematische Bibliographien / Evoluční návrh neuronové sítě / Dissertationen

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Dissertationen zum Thema „Evoluční návrh neuronové sítě“

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Veröffentlicht am 28. Juni 2021

Zuletzt aktualisiert am 1. Februar 2022

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1

Piňos, Michal. „Evoluční návrh konvolučních neuronových sítí“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-417210.

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The aim of this work is to design and implement a program for automated design of convolutional neural networks (CNN) with the use of evolutionary computing techniques. From a practical point of view, this approach reduces the requirements for the human factor in the design of CNN architectures, and thus eliminates the tedious and laborious process of manual design. This work utilizes a special form of genetic programming, called Cartesian genetic programming, which uses a graph representation for candidate solution encoding.This technique enables the user to parameterize the CNN search process and focus on architectures, that are interesting from the view of used computational units, accuracy or number of parameters. The proposed approach was tested on the standardized CIFAR-10dataset, which is often used by researchers to compare the performance of their CNNs. The performed experiments showed, that this approach has both research and practical potential and the implemented program opens up new possibilities in automated CNN design.

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Hytychová, Tereza. „Evoluční návrh neuronových sítí využívající generativní kódování“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445478.

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The aim of this work is to design and implement a method for the evolutionary design of neural networks with generative encoding. The proposed method is based on J. F. Miller's approach and uses a brain model that is gradually developed and which allows extraction of traditional neural networks. The development of the brain is controlled by programs created using cartesian genetic programming. The project was implemented in Python with the use of Numpy library. Experiments have shown that the proposed method is able to construct neural networks that achieve over 90 % accuracy on smaller datasets. The method is also able to develop neural networks capable of solving multiple problems at once while slightly reducing accuracy.

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Svobodová, Jitka. „Neuronové sítě a evoluční algoritmy“. Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-218221.

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Objective of this master's thesis is optimizing of neral network topology using some of evolutionary algorithms. The backpropagation neural network was optimized using genetic algorithms, evolutionary programming and evolutionary strategies. The text contains an application in the Matlab environment which applies these methods to simple tasks as pattern recognition and function prediction. Created graphs of fitness and error functions are included as a result of this thesis.

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Mrnuštík, Michal. „Evoluční návrh využívající booleovské sítě“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237120.

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This master's thesis introduces the Random Boolean Networks as a developmental model in the evolutionary design. The representation of the Random Boolean Networks is described. This representation is combined with an evolutionary algorithm. The genetic operators are described too. The Random Boolean Networks are used as the developmental model for the evolutionary design of the combinational circuits and the sorting networks. Moreover a representation of the Random Boolean Networks for the design of image filters is introduced. The proposed methods are evaluated in different case-studies. The results of the experiments are discussed together with the potential improvements and topics of the next research.

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Pokorný, Petr. „Návrh síťového prvku pomocí neuronové sítě“. Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2008. http://www.nusl.cz/ntk/nusl-228226.

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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.

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Karásek, Štěpán. „Neuronové sítě a genetické algoritmy“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2016. http://www.nusl.cz/ntk/nusl-255370.

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This thesis deals with evolutionary and genetic algorithms and the possible ways of combining them. The theoretical part of the thesis describes genetic algorithms and neural networks. In addition, the possible combinations and existing algorithms are presented. The practical part of this thesis describes the implementation of the algorithm NEAT and the experiments performed. A combination with differential evolution is proposed and tested. Lastly, NEAT is compared to the algorithms backpropagation (for feed-forward neural networks) and backpropagation through time (for recurrent neural networks), which are used for learning neural networks. Comparison is aimed at learning speed, network response quality and their dependence on network size.

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Stískal, Břetislav. „Návrh algoritmů pro neuronové sítě řídicí síťový prvek“. Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217527.

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This diploma thesis is devided into theoretic and practice parts. Theoretic part contains basic information about history and development of Artificial Neural Networks (ANN) from last century till present. Prove of the theoretic section is discussed in the practice part, for example learning, training each types of topology of artificial neural networks on some specifics works. Simulation of this networks and then describing results. Aim of thesis is simulation of the active networks element controlling by artificial neural networks. It means learning, training and simulation of designed neural network. This section contains algorithm of ports switching by address with Hopfield's networks, which used solution of typical Trade Salesman Problem (TSP). Next point is to sketch problems with optimalization and their solutions. Hopfield's topology is compared with Recurrent topology of neural networks (Elman's and Layer Recurrent's topology) their main differents, their advantages and disadvantages and supposed their solution of optimalization in controlling of network's switch. From thesis experience is introduced solution with controll function of ANN in active networks elements in the future.

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Roreček, Pavel. „Evoluční optimalizace konvolučních neuronových sítí“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2018. http://www.nusl.cz/ntk/nusl-385906.

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This Master's Thesis is focused on the principles of neural networks, primarily convolutional neural networks (CNN). It introduces the evolutionary optimization in the context of neural networks. One of existing libraries devoted to the CNN design was chosen (Keras), analysed and used in image classification tasks. An optimization technique based on cartesian genetic programming that should reduce the complexity of CNN's computation was proposed and implemented. The impact of the proposed technique on CNN behaviour was evaluated in a case study.

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Nétková, Barbora. „Evoluční návrh využívající přepisovací systémy“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2016. http://www.nusl.cz/ntk/nusl-255380.

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This master’s thesis proposes a method for the evolutionary design of rewriting systems. In particular, genetic algorithm will be applied to design rewriting rules for a specific variant of Lindenmayer system. The evolved rules of such grammar will be applied to generate growing sorting networks. Some distinct approaches to the rewriting process and construction of the sorting networks will be investigated. It will be shown that the evolution is able to successfully design rewriting rules for the proposed variants of rewriting processes. The results obtained exhibit abilities to successfully create partially growing sorting networks, which was evolved to grow for fewer inputs and in subsequent iterations grows up to 36 inputs.

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Šagát, Martin. „Návrh generativní kompetitivní neuronové sítě pro generování umělých EKG záznamů“. Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2020. http://www.nusl.cz/ntk/nusl-413114.

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The work deals with the generation of ECG signals using generative adversarial networks (GAN). It examines in detail the basics of artificial neural networks and the principles of their operation. It theoretically describes the use and operation and the most common types of failures of generative adversarial networks. In this work, a general procedure of signal preprocessing suitable for GAN training was derived, which was used to compile a database. In this work, a total of 3 different GAN models were designed and implemented. The results of the models were visually displayed and analyzed in detail. Finally, the work comments on the achieved results and suggests further research direction of methods dealing with the generation of ECG signals.

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11

Tomášek, Michal. „Genetický návrh klasifikátoru s využítím neuronových sítí“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2016. http://www.nusl.cz/ntk/nusl-255398.

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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 %.

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12

Zeman, Petr. „Návrh optimalizované vrtule pro bezpilotní prostředky typu multicopter“. Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-400458.

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Výdrž a účinnost multicopterů jsou z velké části ovlivněny výběrem pohonného systému, zejména pak vrtulí. Avšak u malých bezpilotních prostředků, které většinu času stráví ve visu (např. multicoptery), pracují vrtule při nízkých Reynoldsových číslech, případně i v režimu odtržení. Tyto problémy a efekty spojené s rotací jsou řešeny pomocí korekcí aerodynamických koeficientů a aplikovány na vírovou teorii. Tento přístup vede k významnému zvýšení přesnosti výpočtu leteckých vrtulí. Nicméně pro nulovou rychlost nabíhajícího proudu mají tyto korekce tendenci nadhodnocovat hodnoty tahu vrtule. Pro snížení výpočetní náročnosti a času nezbytného k získání potřebných aerodynamických vlastností pro různá Reynoldsova a Machova čísla jsou použity neuronové sítě. Celý proces je implementován do prostředí MATLAB (včetně grafického rozhraní, neuronových sítí a adaptivních algoritmů) a validován na pěti různých vrtulích k prokázání, že vypočtené výkony vrtulí se shodují s experimentálními daty. Variační počet byl vybrán jako metoda pro návrh optimalizované vrtule, jelikož s jeho využitím lze navrhnout vrtuli s maximálním tahem pro zadaný výkon. Pro ověření zvoleného přístupu byla navrhnuta optimalizovaná vrtule, jejíž koeficient tahu je vyšší než odpovídající vrtule, se kterou je srovnávána, při zachování stejné hodnoty koeficientu výkonu.

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13

Peroutka, Lukáš. „Návrh a implementace Data Mining modelu v technologii MS SQL Server“. Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-199081.

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This thesis focuses on design and implementation of a data mining solution with real-world data. The task is analysed, processed and its results evaluated. The mined data set contains study records of students from University of Economics, Prague (VŠE) over the course of past three years. First part of the thesis focuses on theory of data mining, definition of the term, history and development of this particular field. Current best practices and meth-odology are described, as well as methods for determining the quality of data and methods for data pre-processing ahead of the actual data mining task. The most common data mining techniques are introduced, including their basic concepts, advantages and disadvantages. The theoretical basis is then used to implement a concrete data mining solution with educational data. The source data set is described, analysed and some of the data are chosen as input for created models. The solution is based on MS SQL Server data mining platform and it's goal is to find, describe and analyse potential as-sociations and dependencies in data. Results of respective models are evaluated, including their potential added value. Also mentioned are possible extensions and suggestions for further development of the solution.

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Beluský, Ondrej. „Predikce časových řad pomocí statistických metod“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-236962.

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Many companies consider essential to obtain forecast of time series of uncertain variables that influence their decisions and actions. Marketing includes a number of decisions that depend on a reliable forecast. Forecasts are based directly or indirectly on the information derived from historical data. This data may include different patterns - such as trend, horizontal pattern, and cyclical or seasonal pattern. Most methods are based on the recognition of these patterns, their projection into the future and thus create a forecast. Other approaches such as neural networks are black boxes, which uses learning.

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15

KOTNOUR, Tomáš. „Systém pro automatický návrh hasičských vozidel“. Master's thesis, 2019. http://www.nusl.cz/ntk/nusl-394353.

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The topic of this master´s thesis is development of system for configuration of fire truck. The design of the fire truck is based on legislative requirements, future incidents and on a character of landscape. The first part contains these requirements. How to process current incidents and how to predict future incidents is described in the next chapter. For prediction of future incidents are used neural networks are detailed in the third part of the thesis. Implementation of the three selected neural network from previous part for Windows platform is in the fourth part of the thesis. Last part of the thesis is testing several configurations of neural network and the one with the best result is implemented in application which is the main outcome of the thesis.

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16

Misáková, Lucie. „Vliv prostorové rozlišovací schopnosti na výsledky klasifikace dat DPZ, návrh využití pro mapování vegetace“. Doctoral thesis, 2009. http://www.nusl.cz/ntk/nusl-93547.

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17

Klůj, Jan. „Obecná umělá inteligence pro hraní her“. Master's thesis, 2017. http://www.nusl.cz/ntk/nusl-365169.

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Game playing is a relatively interesting task in the field of artificial intelligence in these days. The master thesis deals with general artificial intelligence which is capable of playing selected simple games based on information that is also avai- lable to the human player. Our selected games are 2048, Mario, racing simulator TORCS and Alhambra. All the information acquired by artificial intelligence is provided by games through an interface, therefore none of the models uses visual input. We use evolutionary approaches such as evolutionary algorithms, evolutio- nary strategy CMA and differential evolution applied to different types of neural networks. We are also dealing with deep reinforcement learning. We test these approaches and compare their results. 1

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John, Pavel. „Modelování prostorových vlastností mozkové tkáně“. Master's thesis, 2014. http://www.nusl.cz/ntk/nusl-323075.

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Neural connections in the human brain are known to be modified by experiences. Yet, little is known about the mechanism of the modification and its implications on the brain function. The aim of this thesis is to investigate what impact the spatial properties of brain tissue can have on learning and memory. In particular, we focus on the dendritic plasticity. We present a model where the tissue is represented by a two-dimensional grid and its structure is characterized by various connections between the grid cells. We provide a formal definition of the model and we prove it to be computational as strong as the Turing machine. An adaptation algorithm proposed enables the model to reflect the environmental feedback, while evolutionary algorithms are employed to search for a satisfactory architecture of the model. Implementation is provided and several experiments are driven to demonstrate the key properties of the model. Powered by TCPDF (www.tcpdf.org)

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Švec, Ondřej. „Transformace dat pomocí evolučních algoritmů“. Master's thesis, 2017. http://www.nusl.cz/ntk/nusl-355650.

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In this work, we propose a novel method for a supervised dimensionality reduc- tion, which learns weights of a neural network using an evolutionary algorithm, CMA-ES, optimising the success rate of the k-NN classifier. If no activation func- tions are used in the neural network, the algorithm essentially performs a linear transformation, which can also be used inside of the Mahalanobis distance. There- fore our method can be considered to be a metric learning algorithm. By adding activations to the neural network, the algorithm can learn non-linear transfor- mations as well. We consider reductions to low-dimensional spaces, which are useful for data visualisation, and demonstrate that the resulting projections pro- vide better performance than other dimensionality reduction techniques and also that the visualisations provide better distinctions between the classes in the data thanks to the locality of the k-NN classifier. 1

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SURYNEK, Radek. „Moderní trendy v oboru počítačová fyzika“. Master's thesis, 2013. http://www.nusl.cz/ntk/nusl-136429.

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The theme of the thesis is to make a list few fundamental modern methods which can be used in computerized physics. The thesis describes parallel computing, neural networks,genetic algorithms, fuzzy logic. Every chapter include theoretical description, simplified mathematical expression, proposals of technical solution. Applications are briefly mentioned here too. The printed matter is completed with a few simple examples. The closing part of the thesis acquired information about these methods and outlines their future development.

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