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Dissertations / Theses on the topic 'Neural network MLP'

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Published: 3 June 2025

Last updated: 20 July 2025

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1

Freitas, Luciana Paro Scarin [UNESP]. "Discriminação entre pacientes normais e hemiplégicos utilizando plataforma de força e redes neurais." Universidade Estadual Paulista (UNESP), 2011. http://hdl.handle.net/11449/87051.

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Made available in DSpace on 2014-06-11T19:22:31Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-12-02Bitstream added on 2014-06-13T19:48:52Z : No. of bitstreams: 1 freitas_lps_me_ilha.pdf: 463364 bytes, checksum: 35c3a3450e5ec638595c65e3a7508c09 (MD5)<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)<br>Neste trabalho descreve-se o desenvolvimento de duas redes neurais que identificam e classificam dados da distribuição do peso corporal na região plantar de pessoas normais e hemiplégicas. Esses dados são experimentais e foram obtidos através da utilização de uma p

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Freitas, Luciana Paro Scarin. "Discriminação entre pacientes normais e hemiplégicos utilizando plataforma de força e redes neurais /." Ilha Solteira : [s.n.], 2011. http://hdl.handle.net/11449/87051.

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Orientador: Marcelo Carvalho Minhoto Teixeira<br>Banca: Aparecido Augusto de Carvalho<br>Banca: Márcio Roberto Covacic<br>Resumo: Neste trabalho descreve-se o desenvolvimento de duas redes neurais que identificam e classificam dados da distribuição do peso corporal na região plantar de pessoas normais e hemiplégicas. Esses dados são experimentais e foram obtidos através da utilização de uma plataforma de força contendo 48 sensores. As arquiteturas utilizadas para esta aplicação foram as redes neurais MLP (Multilayer Perceptron) com o algoritmo retropropagação (backpropagation), e ARTMAP Nebulo

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Zhang, Jiaqi. "Accelerating and Predicting Map Projections with CUDA and MLP." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1523394255002174.

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4

Steinholtz, Tim. "Skip connection in a MLP network for Parkinson’s classification." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-303130.

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In this thesis, two different architecture designs of a Multi-Layer Perceptron network have been implemented. One architecture being an ordinary MLP, and in the other adding DenseNet inspired skip connections to an MLP architecture. The models were used and evaluated on the classification task, where the goal was to classify if subjects were diagnosed with Parkinson’s disease or not based on vocal features. The models were trained on an openly available dataset for Parkinson’s classification and evaluated on a hold-out set from this dataset and on two datasets recorded in another sound recordi

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5

Jin, Xin. "Parallel simulation of neural networks on SpiNNaker universal neuromorphic hardware." Thesis, University of Manchester, 2010. https://www.research.manchester.ac.uk/portal/en/theses/parallel-simulation-of-neural-networks-on-spinnaker-universal-neuromorphic-hardware(d6b8b72a-63c4-44ee-963a-ae349b0e379c).html.

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Artificial neural networks have shown great potential and have attracted much research interest. One problem faced when simulating such networks is speed. As the number of neurons increases, the time to simulate and train a network increases dramatically. This makes it difficult to simulate and train a large-scale network system without the support of a high-performance computer system. The solution we present is a "real" parallel system - using a parallel machine to simulate neural networks which are intrinsically parallel applications. SpiNNaker is a scalable massively-parallel computing sys

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Mendes, José da Assunção Gomes. "RECONHECIMENTO DA FALA SUBVOCAL BASEADO EM ELETROMIOGRAFIA DE SUPERFÍCIE (EMG) UTILIZANDO ANÁLISE DE COMPONENTES INDEPENDENTES (ICA) E REDE NEURAL MLP." Universidade Federal do Maranhão, 2007. http://tedebc.ufma.br:8080/jspui/handle/tede/284.

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Made available in DSpace on 2016-08-17T14:52:36Z (GMT). No. of bitstreams: 1 Jose da Assuncao Gomes Mendes.pdf: 1427998 bytes, checksum: 6d9df0350d0b7acb752ecadbcfc1825d (MD5) Previous issue date: 2007-12-19<br>The performance of speech recognition systems is commonly degraded by either speech-related disabilities or by real-world factors such as the environment s noise level and reverberation. In this research, we propose a subvocal speech recognition system based on electromyography (EMG signal) for subvocal acquisition, Independent Component Analysis (ICA) for feature extraction and Neu

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NINA, Diogo Luis Figueiredo. "Análise de Ocorrências em Transformadores do SDEE usando Redes Neurais Artificiais MLP." Universidade Federal do Maranhão, 2012. http://tedebc.ufma.br:8080/jspui/handle/tede/1863.

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Submitted by Maria Aparecida (cidazen@gmail.com) on 2017-08-24T14:18:42Z No. of bitstreams: 1 Diogo Luis.pdf: 4371869 bytes, checksum: adf1274b2033821c3c2a6cca3766a2e6 (MD5)<br>Made available in DSpace on 2017-08-24T14:18:42Z (GMT). No. of bitstreams: 1 Diogo Luis.pdf: 4371869 bytes, checksum: adf1274b2033821c3c2a6cca3766a2e6 (MD5) Previous issue date: 2012-10-03<br>Power system operation and maintenance require attention, precise diagnostics on failure and agility on system recovery. On the other hand, power systems involve high risks, where each operation needs to be carefully planned and

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Bhat, Chandrashekhar. "Artificial Neural Network Approach For Characterization Of Acoustic Emission Sources From Complex Noisy Data." Thesis, Indian Institute of Science, 2001. https://etd.iisc.ac.in/handle/2005/251.

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Safety and reliability are prime concerns in aircraft performance due to the involved costs and risk to lives. Despite the best efforts in design methodology, quality evaluation in production and structural integrity assessment in-service, attainment of one hundred percent safety through development and use of a suitable in-flight health monitoring system is still a farfetched goal. And, evolution of such a system requires, first, identification of an appropriate Technique and next its adoption to meet the challenges posed by newer materials (advanced composites), complex structures and the f

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Bhat, Chandrashekhar. "Artificial Neural Network Approach For Characterization Of Acoustic Emission Sources From Complex Noisy Data." Thesis, Indian Institute of Science, 2001. http://hdl.handle.net/2005/251.

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Safety and reliability are prime concerns in aircraft performance due to the involved costs and risk to lives. Despite the best efforts in design methodology, quality evaluation in production and structural integrity assessment in-service, attainment of one hundred percent safety through development and use of a suitable in-flight health monitoring system is still a farfetched goal. And, evolution of such a system requires, first, identification of an appropriate Technique and next its adoption to meet the challenges posed by newer materials (advanced composites), complex structures and the f

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Ridhagen, Markus, and Petter Lind. "A comparative study of Neural Network Forecasting models on the M4 competition data." Thesis, Uppsala universitet, Statistiska institutionen, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-445568.

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The development of machine learning research has provided statistical innovations and further developments within the field of time series analysis. This study seeks to investigate two different approaches on artificial neural network models based on different learning techniques, and answering how well the neural network approach compares with a basic autoregressive approach, as well as how the artificial neural network models compare to each other. The models were compared and analyzed in regards to the univariate forecast accuracy on 20 randomly drawn time series from two different time fre

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Liberatore, Lorenzo. "Introduction to geometric deep learning and graph neural networks." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amslaurea.unibo.it/25339/.

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This thesis proposes an introduction to the fundamental concepts of supervised deep learning. Starting from Rosemblatt's Perceptron we will discuss the architectures that, in recent years, have revolutioned the world of deep learning: graph neural networks, which led to the formulation of geometric deep learning. We will then give a simple example of graph neural network, discussing the code that composes it and then test our architecture on the MNISTSuperpixels dataset, which is a variation of the benchmark dataset MNIST.

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FERREIRA, Aida Araújo. "Comparação de arquiteturas de redes neurais para sistemas de reconheceimento de padrões em narizes artificiais." Universidade Federal de Pernambuco, 2004. https://repositorio.ufpe.br/handle/123456789/2465.

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Made available in DSpace on 2014-06-12T15:58:28Z (GMT). No. of bitstreams: 2 arquivo4572_1.pdf: 1149011 bytes, checksum: 92aae8f6f9b5145bfcecb94d96dbbc0b (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2004<br>Instituto Federal de Educação, Ciência e Tecnologia de Pernambuco<br>Um nariz artificial é um sistema modular composto de duas partes principais: um sistema sensor, formado de elementos que detectam odores e um sistema de reconhecimento de padrões que classifica os odores detectados. Redes neurais artificiais têm sido utilizadas

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Silva, Marcelo Ribeiro da. "Otimiza??o de superf?cies seletivas de frequ?ncia com elementos pr?-fractais utilizando rede neural MLP e algoritmos de busca populacional." Universidade Federal do Rio Grande do Norte, 2014. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15242.

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Made available in DSpace on 2014-12-17T14:55:18Z (GMT). No. of bitstreams: 1 MarceloRS_TESE.pdf: 2113878 bytes, checksum: 1cc62a66f14cc48f2e97f986a4dbbb8d (MD5) Previous issue date: 2014-01-27<br>Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior<br>This thesis describes design methodologies for frequency selective surfaces (FSSs) composed of periodic arrays of pre-fractals metallic patches on single-layer dielectrics (FR4, RT/duroid). Shapes presented by Sierpinski island and T fractal geometries are exploited to the simple design of efficient band-stop spatial filters with applica

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Goosen, Johannes Christiaan. "Comparing generalized additive neural networks with multilayer perceptrons / Johannes Christiaan Goosen." Thesis, North-West University, 2011. http://hdl.handle.net/10394/5552.

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In this dissertation, generalized additive neural networks (GANNs) and multilayer perceptrons (MLPs) are studied and compared as prediction techniques. MLPs are the most widely used type of artificial neural network (ANN), but are considered black boxes with regard to interpretability. There is currently no simple a priori method to determine the number of hidden neurons in each of the hidden layers of ANNs. Guidelines exist that are either heuristic or based on simulations that are derived from limited experiments. A modified version of the neural network construction with cross–validation sa

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Hedström, Erik, and Philip Wang. "Anomaly Detection using a Deep Learning Multi-layer Perceptron to Mitigate the Risk of Rogue Trading." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301948.

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The term Rogue Trading is defined as the activity of someone at a financial organisation losing a large amount of money in bad or illegal transactions and trying to hide this. The activity of Rogue traders exposes financial organisations to huge risks and may lead to the organisation collapsing, which will affect other stakeholders like, for example, the customers. In order to detect potential Rogue Trading cases, Control Systems that monitor the employees and the positions they take on financial markets must exist. In this study, a two-step control system is suggested to monitor the margins o

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Taco, Pastor Willy Gonzales. "Redes neurais artificiais aplicadas na modelagem individual de padrões de viagens encadeadas a pé." Universidade de São Paulo, 2003. http://www.teses.usp.br/teses/disponiveis/18/18137/tde-18092015-163322/.

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O objetivo deste trabalho foi desenvolver um modelo para reconhecer e reproduzir padrões de viagens encadeadas a pé. O processo de modelagem foi conduzido através da aplicação das técnicas das Redes Neurais Artificiais (RNAs), utilizando-se de uma rede estática MLP e de rede dinâmica Elman. A análise do desempenho do modelo foi baseada nos dados de uma pesquisa de Origem-Destino realizada, em 1987, pelo METRÔ-SP na Região Metropolitana de São Paulo. Na modelagem foi fixado o modo de viagem a pé, e, na abordagem seqüencial, padrões de viagens individuais foram representados em termos de dois co

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17

LOCCI, AMEDEO. "Sviluppo di una piattaforma inerziale terrestre assistita da reti neurali artificiali." Doctoral thesis, Università degli Studi di Roma "Tor Vergata", 2008. http://hdl.handle.net/2108/684.

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Molte delle tecnologie impiegate nei moderni sistemi di ausilio alla navigazione terrestre, risalgono a circa un quarto di secolo. Generalmente, i principali sistemi in uso negli apparati per la navigazione terrestre, risultano essere i Sistemi di Posizionamento Globale (GPS) ed i Sistemi di Navigazione Inerziale (INS). Tali apparati tecnologici, necessitano di componenti fondamentali di qualità più o meno spinta che ne determina costi di mercato progressivamente crescenti, in grado di soddisfare le più diverse applicazioni di navigazione, passando da quella veicolare terrestre, sino a quella

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18

Voiry, Matthieu. "Étude et conception d'un système automatisé de contrôle d'aspect des pièces optiques basé sur des techniques connexionnistes." Thesis, Paris Est, 2008. http://www.theses.fr/2008PEST0077/document.

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Dans différents domaines industriels, la problématique du diagnostic prend une place importante. Ainsi, le contrôle d’aspect des composants optiques est une étape incontournable pour garantir leurs performances opérationnelles. La méthode conventionnelle de contrôle par un opérateur humain souffre de limitations importantes qui deviennent insurmontables pour certaines optiques hautes performances. Dans ce contexte, cette thèse traite de la conception d’un système automatique capable d’assurer le contrôle d’aspect. Premièrement, une étude des capteurs pouvant être mis en oeuvre par ce système e

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Buttar, Sarpreet Singh. "Applying Artificial Neural Networks to Reduce the Adaptation Space in Self-Adaptive Systems : an exploratory work." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-87117.

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Self-adaptive systems have limited time to adjust their configurations whenever their adaptation goals, i.e., quality requirements, are violated due to some runtime uncertainties. Within the available time, they need to analyze their adaptation space, i.e., a set of configurations, to find the best adaptation option, i.e., configuration, that can achieve their adaptation goals. Existing formal analysis approaches find the best adaptation option by analyzing the entire adaptation space. However, exhaustive analysis requires time and resources and is therefore only efficient when the adaptation

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Guo, Zhihao. "Intelligent multiple objective proactive routing in MANET with predictions on delay, energy, and link lifetime." online version, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=case1195705509.

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Bolognini, Damiano. "Improving the convergence speed of NeRFs with depth supervision and weight initialization." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amslaurea.unibo.it/25656/.

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Neural rendering is a new and developing field where computer graphics and deep learning techniques are combined to generate photo-realistic images using deep neural networks. In particular, Neural Radiance Fields (NeRF) is able to synthesise novel views of a scene with unprecedented quality by fitting a Multi-Layer Perceptron (MLP) to RGB images. However, training this network requires plenty of time and computation even on modern GPUs, making this new technology hardly employable on practical specialized applications. In this project, we show that employing the known depth of the scen

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Fernando, Thudugala Mudalige K. G. "Hydrological applications of MLP neural networks with back-propagation." Thesis, Hong Kong : University of Hong Kong, 2002. http://sunzi.lib.hku.hk/hkuto/record.jsp?B25085517.

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Machek, Ondřej. "Fuzzy modely map pro pohyb mobilních robotů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2011. http://www.nusl.cz/ntk/nusl-219349.

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This master thesis present a method for building topological maps for mobile robot navigation using neural network and neural fuzzy network. The master thesis concentrates on classification method. Neural fuzzy network is compared with two neural networks. It was also designed control algorithm exploration environment for autonomous mobile robot. This will rereduce the time to build the map. I developed simulation program in Matlab, which simulate move mobile robot in unknown environment.

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Gaspar, Thiago Lombardi. "Reconhecimento de faces humanas usando redes neurais MLP." Universidade de São Paulo, 2006. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-27042006-231620/.

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O objetivo deste trabalho foi desenvolver um algoritmo baseado em redes neurais para o reconhecimento facial. O algoritmo contém dois módulos principais, um módulo para a extração de características e um módulo para o reconhecimento facial, sendo aplicado sobre imagens digitais nas quais a face foi previamente detectada. O método utilizado para a extração de características baseia-se na aplicação de assinaturas horizontais e verticais para localizar os componentes faciais (olhos e nariz) e definir a posição desses componentes. Como entrada foram utilizadas imagens faciais de três bancos distin

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Fraticelli, Chiara. "Λc reconstruction with artificial neural networks". Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/19985/.

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Il rivelatore ALICE studia collisioni di ioni pesanti ultrarelativistici in modo da creare e di conseguenza studiare lo stato della materia chiamato plasma di quark e gluoni. Questo obiettivo risulta difficoltoso data la sua vita breve, quindi facciamo riferimento a misure indirette per la prova della sua esistenza. In questa tesi abbiamo sfruttato tecniche di machine learning per studiare il decadimento del barione charmato Λc per dedurre alcune sue proprietà. In particolare abbiamo usato il metodo delle reti neurali per ricavare tutte le informazioni possibili con la tecninca di un'analisi m

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Turner, Joseph Vernon. "Application of Artificial Neural Networks in Pharmacokinetics." Thesis, The University of Sydney, 2003. http://hdl.handle.net/2123/488.

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Drug development is a long and expensive process. It is often not until potential drug candidates are administered to humans that accurate quantification of their pharmacokinetic characteristics is achieved. The goal of developing quantitative structure-pharmacokinetic relationships (QSPkRs) is to relate the molecular structure of a chemical entity with its pharmacokinetic characteristics. In this thesis artificial neural networks (ANNs) were used to construct in silico predictive QSPkRs for various pharmacokinetic parameters using different drug data sets. Drug pharmacokinetic data for all s

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Turner, Joseph Vernon. "Application of Artificial Neural Networks in Pharmacokinetics." University of Sydney, 2003. http://hdl.handle.net/2123/488.

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Drug development is a long and expensive process. It is often not until potential drug candidates are administered to humans that accurate quantification of their pharmacokinetic characteristics is achieved. The goal of developing quantitative structure-pharmacokinetic relationships (QSPkRs) is to relate the molecular structure of a chemical entity with its pharmacokinetic characteristics. In this thesis artificial neural networks (ANNs) were used to construct in silico predictive QSPkRs for various pharmacokinetic parameters using different drug data sets. Drug pharmacokinetic data for all s

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Rendel, Mark. "Neural network structure in an exhaustive RNA genotype-phenotype map." Thesis, University of Oxford, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.494400.

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Winter, Marylin. "Artificial neural networks and map-matching for GPS navigation." Thesis, University of South Wales, 2006. https://pure.southwales.ac.uk/en/studentthesis/artificial-neural-networks-and-mapmatching-for-gps-navigation(67bf2a4a-fcd2-4a86-8895-0ed296461bc5).html.

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Global navigation satellite systems (GNSS), such as the Global Positioning System (GPS) have been increasingly used in navigation and tracking of vehicles. Using GPS, certain positioning errors and limitations, such as multipath effects and the geometric position of the satellites (DOP) or signal obstructions by high buildings, trees and terrain, have to be considered. Generally travel on road or footpath, map-matching algorithms can be used to correlate the computed system location with a digital map network. Map Matched GPS (MMGPS) is a test-bed simulator for researching algorithms and techn

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Lam, Yiu Man. "Self-organized cortical map formation by guiding connections /." View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202005%20LAM.

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Rahman, Sardar Muhammad Monzurur, and mrahman99@yahoo com. "Data Mining Using Neural Networks." RMIT University. Electrical & Computer Engineering, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080813.094814.

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Data mining is about the search for relationships and global patterns in large databases that are increasing in size. Data mining is beneficial for anyone who has a huge amount of data, for example, customer and business data, transaction, marketing, financial, manufacturing and web data etc. The results of data mining are also referred to as knowledge in the form of rules, regularities and constraints. Rule mining is one of the popular data mining methods since rules provide concise statements of potentially important information that is easily understood by end users and also actionable pat

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Lundström, Christoffer, and Camilla Heiding. "Predictive Autoscaling of Systems using Artificial Neural Networks." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-104714.

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Autoscalers handle the scaling of instances in a system automatically based on specified thresholds such as CPU utilization. Reactive autoscalers do not take the delay of initiating a new instance into account, which may lead to overutilization. By applying machine learning methodology to predict future loads and the desired number of instances, it is possible to preemptively initiate scaling such that new instances are available before demand occurs. Leveraging efficient scaling policies keeps the costs and energy consumption low while ensuring the availability of the system. In this thesis,

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Ferro, Luciano [UNESP]. "Aplicação da rede neural MLP (Multilayer Perceptron) em indústria de pisos e revestimentos do Pólo Cerâmico de Santa Gertrudes - SP." Universidade Estadual Paulista (UNESP), 2013. http://hdl.handle.net/11449/102925.

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Made available in DSpace on 2014-06-11T19:32:18Z (GMT). No. of bitstreams: 0 Previous issue date: 2013-04-25Bitstream added on 2014-06-13T19:21:52Z : No. of bitstreams: 1 ferro_l_dr_rcla.pdf: 507040 bytes, checksum: 8569d113b387622fd192e005a1bbf02b (MD5)<br>As Redes Neurais Artificiais se constituem numa alternativa à computação programada tradicional e foram aplicadas em quase todos os ramos do conhecimento humano. Em Geotecnologia, no entanto, ainda são escassas as aplicações de maneira que, com este trabalho, procura-se mostrar que elas também podem ser aplicadas em indústrias de pisos e

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Ferro, Luciano. "Aplicação da rede neural MLP (Multilayer Perceptron) em indústria de pisos e revestimentos do Pólo Cerâmico de Santa Gertrudes - SP /." Rio Claro, 2013. http://hdl.handle.net/11449/102925.

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Orientador: José Ricardo Sturaro<br>Banca: Paulo Milton Barbosa Landim<br>Banca: Ricardo Egydio de Carvalho<br>Banca: Alessandro Firmiano de Jesus<br>Banca: Alexandre Campane Vidal<br>Resumo: As Redes Neurais Artificiais se constituem numa alternativa à computação programada tradicional e foram aplicadas em quase todos os ramos do conhecimento humano. Em Geotecnologia, no entanto, ainda são escassas as aplicações de maneira que, com este trabalho, procura-se mostrar que elas também podem ser aplicadas em indústrias de pisos e revestimentos cerâmicos do Pólo Cerâmico de Santa Gertrudes, Estado

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Miranda, André Pacheco. "Previsão do mercado acionário por meio de redes neurais mlp e redes neurais kohonen em período de crise econômica." Universidade Federal de Santa Maria, 2013. http://repositorio.ufsm.br/handle/1/4651.

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Fluctuations in the stock market through economic crises, risks of deflation and liquidity traps are critical in the analysis of risk, which cause discrepancies in the execution of a particular scope in the equities market. The crisis in subprime insolvency in 2007/2008 which had a major impact on financial markets founded further discussions in relation to risk control in the decision making of investors. In the stock market risk analysis seeks to assist the investor in making decisions, for it makes use of statistical methods and tools to try to predict market movements. Based on these and p

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Porenius, Oscar, and Nils Hansson. "Using machine learning to help find paths through the map in Slay the Spire." Thesis, Malmö universitet, Institutionen för datavetenskap och medieteknik (DVMT), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43386.

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Slay the Spire is a complex deck-building and roguelike game with many possibilities of improving players ability to win. An important part of Slay the Spire is choosing a path that makes the players character as successful as possible. In this study we show that machine learning can help players pick better paths by creating an Artificial Neural Network (ANN) that predicts the most successful path of all available paths, we also discuss what makes a path successful. This study performed two experiments, one user study and one simulation experiment, with the intention of evaluating the created

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Martins, João Roberto Deroco. "Detecção e classificação de curto-circuitos em sistemas de distribuição usando rede neural artificial ARTMAP nebulosa /." Ilha Solteira : [s.n.], 2010. http://hdl.handle.net/11449/87047.

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Orientador: Jozué Vieira Filho<br>Banca: Anna Diva Plasencia Lotufo<br>Banca: Marco Aparecido Queiroz Duarte<br>Resumo: Este trabalho apresenta uma metodologia para detecção e classificação de faltas do tipo curto-circuito. Esta operação de diagnóstico tem como principal operador um banco de redes neurais artificiais (RNAs) do tipo ARTMAP Nebulosa. Tal ferramenta segue a principal filosofia das RNAs: o reconhecimento de padrões, através de um trei- namento supervisionado inicial, responsável por atualizar os parâmetros das redes con- comitantemente com os resultados desejados. Finalizada a fas

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Ferroni, Nicola. "Exact Combinatorial Optimization with Graph Convolutional Neural Networks." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/17502/.

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Combinatorial optimization problems are typically tackled by the branch-and-bound paradigm. We propose to learn a variable selection policy for branch-and-bound in mixed-integer linear programming, by imitation learning on a diversified variant of the strong branching expert rule. We encode states as bipartite graphs and parameterize the policy as a graph convolutional neural network. Experiments on a series of synthetic problems demonstrate that our approach produces policies that can improve upon expert-designed branching rules on large problems, and generalize to instances significantly lar

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Gouveia, Wellington da Rocha. "Detecção de faces humanas em imagens coloridas utilizando redes neurais artificiais." Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/18/18152/tde-11032010-160048/.

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A tarefa de encontrar faces em imagens é extremamente complexa, pois pode ocorrer variação de luminosidade, fundos extremamente complexos e objetos que podem se sobrepor parcialmente à face que será localizada, entre outros problemas. Com o avanço na área de visão computacional técnicas mais recentes de processamento de imagens e inteligência artificial têm sido combinadas para desenvolver algoritmos mais eficientes para a tarefa de detecção de faces. Este trabalho apresenta uma metodologia de visão computacional que utiliza redes neurais MLP (Perceptron Multicamadas) para segmentar a cor da p

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Barlow, Peter A. "A non-invasive technique for the diagnosis of temporomandibular joint disorders." Thesis, University of Sussex, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296542.

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Maron, Guilherme. "Analysis and classification of spatial cognition using non-linear analysis and artificial neural networks." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2014. http://hdl.handle.net/10183/88901.

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O principal objetivo do presente trabalho é propor, desenvolver, testar e apresentar um método para a classificação do grau de desenvolvimento da capacidade cognitiva espacial de diferentes indivíduos. 37 alunos de graduação tiveram seus eletroencefalogramas (EEGs) capturados enquanto estavam engajados em tarefas de rotação mental de imagens tridimensionais. Seu grau de desenvolvimento da capacidade cognitiva espacial foi avaliado utilizando-se um teste psicológico BPR-5. O maior expoente de Lyapunov (LLE) foi calculado a partir de cada um dos 8 canais dos EEGs capturados. OS LLEs foram então

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Martins, João Roberto Deroco [UNESP]. "Detecção e classificação de curto-circuitos em sistemas de distribuição usando rede neural artificial ARTMAP nebulosa." Universidade Estadual Paulista (UNESP), 2010. http://hdl.handle.net/11449/87047.

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Made available in DSpace on 2014-06-11T19:22:31Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-02-19Bitstream added on 2014-06-13T20:09:42Z : No. of bitstreams: 1 martins_jrd_me_ilha.pdf: 2522090 bytes, checksum: f59e117ff382b22406c99cdc0096ef37 (MD5)<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)<br>Este trabalho apresenta uma metodologia para detecção e classificação de faltas do tipo curto-circuito. Esta operação de diagnóstico tem como principal operador um banco de redes neurais artificiais (RNAs) do tipo ARTMAP Nebulosa. Tal ferramenta segue a principal

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Cranston, Daniel, and Filip Skarfelt. "Normalized Convolution Network and Dataset Generation for Refining Stereo Disparity Maps." Thesis, Linköpings universitet, Datorseende, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158449.

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Finding disparity maps between stereo images is a well studied topic within computer vision. While both classical and machine learning approaches exist in the literature, they frequently struggle to correctly solve the disparity in regions with low texture, sharp edges or occlusions. Finding approximate solutions to these problem areas is frequently referred to as disparity refinement, and is usually carried out separately after an initial disparity map has been generated. In the recent literature, the use of Normalized Convolution in Convolutional Neural Networks have shown remarkable results

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Loiola, Rafael Gomes. "PREVISÃO DE SÉRIES TEMPORAIS EM UMA INDÚSTRIA METAL MECÂNICA UTILIZANDO MÉTODO CLÁSSICO DE BOX-JENKINS E REDES NEURAIS ARTIFICIAIS MLP." Pontifícia Universidade Católica de Goiás, 2016. http://localhost:8080/tede/handle/tede/2486.

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Made available in DSpace on 2016-08-10T10:40:42Z (GMT). No. of bitstreams: 1 RAFAEL GOMES LOIOLA.pdf: 2193685 bytes, checksum: 77fe8f4c3a881108732f58c6013d52b5 (MD5) Previous issue date: 2016-03-09<br>The demand forecasting is of essential importance for business environments, in a way to serve as a decision making supporting tool during the development of companies strategic planning. This work strived to compare statistics with artificial intelligence methods applied to provisioning on demand issues using temporal series through Box-Jenkins and Artificial Neural Networks Multilayer Percept

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Ahamd, Usman Aliyu. "Automated data classification using feature weighted self-organising map (FWSOM)." Thesis, University of Aberdeen, 2018. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=239342.

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The enormous increase in the production of electronic data in today's information era has led to more challenges in analysing and understanding of the data. The rise in the innovations of technology devices, computers and the Internet has made it much easier to collect and store different kind of data ranging from personal, medical, financial, and scientific data. The growth in the amount of the generated data has introduced the term “Big Data” to describe this extremely high-dimensional and yet complex data. Making sense of the generated data sets is of great importance for the discovery of m

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Young, Ryan F. "Utilization of a Neural Network to Improve Fuel Maps of an Air-Cooled Internal Combustion Engine." Ohio University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1282143527.

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Verì, Daniele. "Empirical Model Learning for Constrained Black Box Optimization." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amslaurea.unibo.it/25704/.

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Black box optimization is a field of the global optimization which consists in a family of methods intended to minimize or maximize an objective function that doesn’t allow the exploitation of gradients, linearity or convexity information. Beside that the objective is often a problem that requires a significant amount of time/resources to query a point and thus the goal is to go as close as possible to the optimum with the less number of iterations possible. The Emprical Model Learning is a methodology for merging Machine Learning and optimization techniques like Constraint Programming

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PRONO, LUCIANO. "Methods and Applications for Low-power Deep Neural Networks on Edge Devices." Doctoral thesis, Politecnico di Torino, 2023. https://hdl.handle.net/11583/2976593.

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Fiscone, Cristiana. "A machine learning approach to QSM: quantitative susceptibility map reconstruction with convolutional autoencoders." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18047/.

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QSM (Quantitative Susceptibility Mapping) è un’ applicazione MRI, in grado di riprodurre, partendo da dati di fase di sequenze gradient echo, distribuzioni di suscettività magnetica dei tessuti. Con questa tecnica è possibile, ad esempio, caratterizzare e trattare malattie vascolari e neurodegenerative. Per ottenere la mappa di suscettività, deve essere risolto un problema mal posto, dovuto alla presenza di singolarità all'interno dello spazio di Fourier. Sono state già implementate diverse tecniche per superare questa difficoltà, divise in: single-orientation methods (e.g. TKD) e multiple-

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Jacobs, William. "COMBINAÇÃO DAS PREVISÕES DOS MODELOS DE BOX-JENKINS E MLP/RNA PARA A PREVISÃO DE DEMANDA NO PLANEJAMENTO DA PRODUÇÃO." Universidade Federal de Santa Maria, 2014. http://repositorio.ufsm.br/handle/1/8327.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>A forecast of future demand for the products is the main variable to be considered in the planning and in production control in organizations. Two methods of time series forecasting often used in the literature are the ARIMA and MLP/RNA models. A practice that began in 1969 and has consolidated for greater accuracy is the combination of individual forecasts from two or more models. Considering the need for organizations by predictive techniques that generate better results, this study aims to predict the future values of a time ser

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