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Relevant bibliographies by topics / Artificial neural networks / Dissertations / Theses

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Dissertations / Theses on the topic 'Artificial neural networks'

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Published: 4 June 2021

Last updated: 25 July 2025

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1

Boychenko, I. V., and G. I. Litvinenko. "Artificial neural networks." Thesis, Вид-во СумДУ, 2009. http://essuir.sumdu.edu.ua/handle/123456789/17044.

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2

Menneer, Tamaryn Stable Ia. "Quantum artificial neural networks." Thesis, University of Exeter, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286530.

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3

Chambers, Mark Andrew. "Queuing network construction using artificial neural networks /." The Ohio State University, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488193665234291.

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4

Orr, Ewan. "Evolving Turing's Artificial Neural Networks." Thesis, University of Canterbury. Department of Physics and Astronomy, 2010. http://hdl.handle.net/10092/4620.

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Our project uses ideas first presented by Alan Turing. Turing's immense contribution to mathematics and computer science is widely known, but his pioneering work in artificial intelligence is relatively unknown. In the late 1940s Turing introduced discrete Boolean artificial neural networks and, it has been argued that, he suggested that these networks be trained via evolutionary algorithms. Both artificial neural networks and evolutionary algorithms are active fields of research. Turing's networks are very basic yet capable of complex tasks such as processing sequential input; consequently, t

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5

Varoonchotikul, Pichaid. "Flood forecasting using artificial neural networks /." Lisse : Balkema, 2003. http://www.e-streams.com/es0704/es0704_3168.html.

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6

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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7

Millevik, Daniel, and Michael Wang. "Stock Forecasting Using Artificial Neural Networks." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166455.

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This paper studies the potential of artificial neural networks (ANNs) in stock forecasting. It also investigates how the number of neurons in the network, as well as the distribution of the training data into training, validation and testing sets, affect the accuracy of the network. By using MATLAB and its Neural Network Toolbox tests were carried out with a two-layer feedforward neural network (FFNN). These are carried out by collecting five years of historical data from the Dow Jones Industrial Average (DJIA) stock index, which is then used for training the network. Finally, retraining the n

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8

Prasad, Jayan Ganesh Information Technology &amp Electrical Engineering Australian Defence Force Academy UNSW. "Financial forecasting using artificial neural networks." Awarded by:University of New South Wales - Australian Defence Force Academy. School of Information Technology and Electrical Engineering, 2008. http://handle.unsw.edu.au/1959.4/38700.

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Despite the extent of a theoretical framework in financial market studies, a vast majority of the traders, investors and computer scientists have relied only on technical and timeseries data for predicting future prices. So far, the forecasting models have rarely incorporated macro-economic and market fundamentals successfully, especially with short-term predictions ranging less than a month. In this investigation on the predictability of certain financial markets, an attempt has been made to incorporate a un-exampled and encompassing set of parameters into an Artificial Neural Network predict

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9

Ng, Roger K. W. "Rapid prototyping of artificial neural networks." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq23440.pdf.

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10

Hook, Jaroslav. "Are artificial neural networks learning machines?" Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ38651.pdf.

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11

Coulibaly, Paulin. "Artificial neural networks for hydrological forecasting." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0028/NQ52236.pdf.

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12

Baker, Thomas Edward. "Implementation limits for artificial neural networks." Full text open access at:, 1990. http://content.ohsu.edu/u?/etd,268.

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13

Garvin, Alan David Morris. "Self-structuring of artificial neural networks." Thesis, University of Cambridge, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307948.

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14

Watkins, Bruce E. "Data compression using artificial neural networks." Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/25801.

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Approved for public release; distribution is unlimited<br>This thesis investigates the application of artificial neural networks for the compression of image data. An algorithm is developed using the competitive learning paradigm which takes advantage of the parallel processing and classification capability of neural networks to produce an efficient implementation of vector quantization. Multi-Stage, tree searched, and classification vector quantization codebook design techniques are adapted to the neural network design to reduce the computational cost and hardware requirements. The resu

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15

Gulliford, Sarah Louise. "Artificial neural networks applied to radiotherapy." Thesis, Institute of Cancer Research (University Of London), 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.404474.

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16

Townsend, Joseph Paul. "Artificial development of neural-symbolic networks." Thesis, University of Exeter, 2014. http://hdl.handle.net/10871/15162.

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Artificial neural networks (ANNs) and logic programs have both been suggested as means of modelling human cognition. While ANNs are adaptable and relatively noise resistant, the information they represent is distributed across various neurons and is therefore difficult to interpret. On the contrary, symbolic systems such as logic programs are interpretable but less adaptable. Human cognition is performed in a network of biological neurons and yet is capable of representing symbols, and therefore an ideal model would combine the strengths of the two approaches. This is the goal of Neural-Symbol

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17

Zhong, Xiaolin. "Robot calibration using artificial neural networks." Thesis, Edinburgh Napier University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295387.

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18

Lukashev, A. "Basics of artificial neural networks (ANNs)." Thesis, Київський національний університет технологій та дизайну, 2018. https://er.knutd.edu.ua/handle/123456789/11353.

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19

Rodríguez, Villegas Antoni. "Polyp segmentation using artificial neural networks." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-98001.

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Colorectal cancer is the second cause of cancer death in the world. Aiming to early detect and prevent this type of cancer, clinicians perform screenings through the colon searching for polyps (colorectal cancer precursor lesions).If found, these lesions are susceptible of being removed in order to further ana-lyze their malignancy degree. Automatic polyp segmentation is of primary impor-tance when it comes to computer-aided medical diagnosis using images obtained in colonoscopy screenings. These results allow for more precise medical diagnosis which can lead to earlier detection.This project

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20

Lind, Benjamin. "Artificial Neural Networks for Image Improvement." Thesis, Linköpings universitet, Datorseende, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-137661.

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After a digital photo has been taken by a camera, it can be manipulated to be more appealing. Two ways of doing that are to reduce noise and to increase the saturation. With time and skills in an image manipulating program, this is usually done by hand. In this thesis, automatic image improvement based on artificial neural networks is explored and evaluated qualitatively and quantitatively. A new approach, which builds on an existing method for colorizing gray scale images is presented and its performance compared both to simpler methods and the state of the art in image denoising. Saturation

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21

Miranda, Trujillo Luis Carlos. "Artificial Neural Networks in Greenhouse Modelling." Doctoral thesis, Humboldt-Universität zu Berlin, 2018. http://dx.doi.org/10.18452/19354.

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Moderne Präzisionsgartenbaulicheproduktion schließt hoch technifizierte Gewächshäuser, deren Einsatz in großem Maße von der Qualität der Sensorik- und Regelungstechnik abhängt, mit ein. Zu den Regelungsstrategien gehören unter anderem Methoden der Künstlichen Intelligenz, wie z.B. Künstliche Neuronale Netze (KNN, aus dem Englischen). Die vorliegende Arbeit befasst sich mit der Eignung KNN-basierter Modelle als Bauelemente von Klimaregelungstrategien in Gewächshäusern. Es werden zwei Modelle vorgestellt: Ein Modell zur kurzzeitigen Voraussage des Gewächshausklimas (Lufttemperatur und relative

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22

Guiga, Linda. "Software protections for artificial neural networks." Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAT024.

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Les réseaux de neurones (NNs) sont très présents dans notre vie quotidienne, à travers les smartphones, la reconnaissance faciale et biométrique ou même le domaine médical. Leur sécurité est donc de la plus haute importance. Si de tels modèles fuitent, cela mettrait non seulement en péril la confidentialité de données sensibles, mais porterait aussi atteinte à la propriété intellectuelle. La sélection d’une architecture adaptée et l'entraînement de ses paramètres prennent du temps - parfois des mois -- et nécessitent d'importantes ressources informatiques. C'est pourquoi un NN constitue une pr

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23

Bolt, George Ravuama. "Fault tolerance in artificial neural networks : are neural networks inherently fault tolerant?" Thesis, University of York, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.317683.

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24

NAPOLI, CHRISTIAN. "A-I: Artificial intelligence." Doctoral thesis, Università degli studi di Catania, 2016. http://hdl.handle.net/20.500.11769/490996.

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In this thesis we proposed new neural architectures and information theory approaches. By means of wavelet analysis, neural networks, and the results of our own creations, namely the wavelet recurrent neural networks and the radial basis probabilistic neural networks,we tried to better understand, model and cope with the human behavior itself. The first idea was to model the workers of a crowdsourcing project as nodes on a cloud-computing system, we also hope to have exceeded the limits of such a definition. We hope to have opened a door on new possibilities to model the behavior of socially i

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25

Lindefelt, Lisa. "Predicting gene expression using artificial neural networks." Thesis, University of Skövde, Department of Computer Science, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-707.

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<p>Today one of the greatest aims within the area of bioinformatics is to gain a complete understanding of the functionality of genes and the systems behind gene regulation. Regulatory relationships among genes seem to be of a complex nature since transcriptional control is the result of complex networks interpreting a variety of inputs. It is therefore essential to develop analytical tools detecting complex genetic relationships.</p><p>This project examines the possibility of the data mining technique artificial neural network (ANN) detecting regulatory relationships between genes. As an init

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26

Cavaco, Philip. "Artificial Grammar Recognition Using Spiking Neural Networks." Thesis, Mälardalen University, School of Innovation, Design and Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-5875.

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<p>This thesis explores the feasibility of Artificial Grammar (AG) recognition using spiking neural networks. A biologically inspired minicolumn model is designed as the base computational unit. Two network topographies are defined with different ideologies. Both networks consists of minicolumn models, referred to as nodes, connected with excitatory and inhibitory connections. The first network contains nodes for every bigram and trigram producible by the grammar’s finite state machine (FSM). The second network has only nodes required to identify unique internal states of the FSM. The networks

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27

Guler, Altug. "Seismic Vulnerability Assessment Using Artificial Neural Networks." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606067/index.pdf.

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In this study, an alternative seismic vulnerability assessment model is developed. For this purpose, one of the most popular artificial intelligence techniques, Artificial Neural Network (ANN), is used. Many ANN models are generated using 4 different network training functions, 1 to 50 hidden neurons and combination of structural parameters like number of stories, normalized redundancy scores, overhang ratios, soft story indices, normalized total column areas, normalized total wall areas are used to achieve the best assessment performance. Duzce database is used throughout the thesis for tra

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28

Frøyen, Even Bruvik. "Exploring Learning in Evolutionary Artificial Neural Networks." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-15689.

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Evolutionary artificial neural networks can adapt to new circumstances, and handle slight changes without catastrophic failure. However, under constantly changing circumstances, resulting in unpredictable grounds for evaluating success, the lack of memory of previous adaptations are a limiting factor. While further evolution can allow adaptations to new changes, the same is required for a return to a previous environment. To reduce the need for further evolution to deal with previously seen problems, this thesis looks at an approach to encourage previous knowledge to be retained across generat

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29

Turner, Joe. "Application of artificial neural networks in pharmacokinetics /." Connect to full text, 2003. http://setis.library.usyd.edu.au/adt/public_html/adt-NU/public/adt-NU20031007.090937/index.html.

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30

Gou, Zhenkun. "Canonical correlation analysis and artificial neural networks." Thesis, University of the West of Scotland, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269409.

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31

Hasan, Usama. "Artificial neural networks for voltage collapse monitoring." Thesis, Imperial College London, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286623.

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32

Porter, Nicholas David. "Facial feature processing using artificial neural networks." Thesis, University of Warwick, 1998. http://wrap.warwick.ac.uk/59539/.

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Describing a human face is a natural ability used in eveyday life. To the police, a witness description of a suspect is key evidence in the identification of the suspect. However, the process of examining "mug shots" to find a match to the description is tedious and often unfruitful. If a description could be stored with each photograph and used as a searchable index, this would provide a much more effective means of using "mug shots" for identification purposes. A set of descriptive measures have been defined by Shepherd [73] which seek to describe faces in a manner that may be used for just

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33

Muthuraman, Sethuraman. "The evolution of modular artificial neural networks." Thesis, Robert Gordon University, 2005. http://hdl.handle.net/10059/284.

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This thesis describes a novel approach to the evolution of Modular Artificial Neural Networks. Standard Evolutionary Algorithms, used in this application include: Genetic Algorithms, Evolutionary Strategies, Evolutionary Programming and Genetic Programming; however, these often fail in the evolution of complex systems, particularly when such systems involve multi-domain sensory information which interacts in complex ways with system outputs. The aim in this work is to produce an evolutionary method that allows the structure of the network to evolve from simple to complex as it interacts with a

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34

Chen, Jian-Rong. "Theory and applications of artificial neural networks." Thesis, Durham University, 1991. http://etheses.dur.ac.uk/6240/.

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In this thesis some fundamental theoretical problems about artificial neural networks and their application in communication and control systems are discussed. We consider the convergence properties of the Back-Propagation algorithm which is widely used for training of artificial neural networks, and two stepsize variation techniques are proposed to accelerate convergence. Simulation results demonstrate significant improvement over conventional Back-Propagation algorithms. We also discuss the relationship between generalization performance of artificial neural networks and their structure and

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35

D'Souza, Winston Anthony. "Real-time applications of artificial neural networks." Thesis, University of Aberdeen, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445136.

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This research takes an innovative look at two distinct applications of Artificial Neural Networks (ANNs) concerning the manipulation of data within real-time systems. The first contribution of this research involves the filtering of errors associated with data emergent from Inertial Navigation Systems (INS) by adopting an ANN filter. This novel approach when compared to present day optimal estimation filter techniques for random data such as the Kalman Filter (KF) and its variants, offers a better estimated response without the need to mathematically model error. In addition to this advantag

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36

Zhu, Kangmin. "ECG feature recognition using artificial neural networks." Thesis, University of Essex, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.316072.

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37

Kurd, Zeshan. "Artificial neural networks in safety-critical applications." Thesis, University of York, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.428472.

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38

Rust, Alistair Gibson. "Developmental self-organisation in artificial neural networks." Thesis, University of Hertfordshire, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.268042.

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39

Ferguson, Alistair. "Learning in RAM-based artificial neural networks." Thesis, University of Hertfordshire, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283866.

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40

Berry, Ian Michael. "Data classification using unsupervised artificial neural networks." Thesis, University of Sussex, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.390079.

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41

Gavrilov, Alexander I. "Welding process engineering with artificial neural networks." Thesis, De Montfort University, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.420851.

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42

ABELEM, ANTONIO JORGE GOMES. "ARTIFICIAL NEURAL NETWORKS IN TIME SERIES FORECASTING." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1994. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8489@1.

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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>Esta dissertação investiga a utilização de Redes Neurais Artificiais (RNAs) na previsão de séries temporais, em particular de séries financeiras, consideradas uma classe especial de séries temporais, caracteristicamente ruídos e sem periodicidade aparente. O trabalho envolve quatro partes principais: um estudo sobre redes neurais artificiais e séries temporais; a modelagem das RNAs para previsão de séries temporais; o desenvolvimento de um ambiente de simulação; e o estudo de caso. No estudo sobre Redes Neurais Artificiais

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43

Han, Ying. "Analysing time series using artificial neural networks." Thesis, University of the West of Scotland, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.398318.

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44

Kendall, Gary David. "Non-linear modelling through artificial neural networks." Thesis, King's College London (University of London), 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.300608.

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45

Nordström, Tomas. "Highly parallel computers for artificial neural networks." Doctoral thesis, Luleå tekniska universitet, 1995. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-25655.

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During a number of years the two fields of artificial neural networks (ANNs) and highly parallel computing have both evolved rapidly. In this thesis the possibility of combining these fields is explored, investigating the design and usage of highly parallel computers for ANN calculations. A new system-architecture REMAP (Real-time, Embedded, Modular, Adaptive, Parallel processor) is presented as a candidate platform for future action-oriented systems. With this new system-architecture, multi-modular networks of cooperating and competing ANNs can be realized. For action-oriented systems, concep

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46

Vieira, Cristiano Ribeiro. "Forecasting financial markets with artificial neural networks." Master's thesis, Instituto Superior de Economia e Gestão, 2013. http://hdl.handle.net/10400.5/6340.

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Mestrado em Matemática Financeira<br>Artificial Neural Networks are exible nonlinear mathematical models widely used in forecasting. This work is intended to investigate the support these models can give to nancial economists predicting prices movements of oil and gas companies listed in stock exchanges. Multilayer Perceptron models with logistic activation functions achieved better results predicting the direction of stocks returns than traditional linear regressions and better performances in companies with lower market capitalization. Furthermore, multilayer perceptron with eight hidden un

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47

Dermelov, D. O. "Artificial neural networks in self-driving cars." Thesis, Київський національний університет технологій та дизайну, 2019. https://er.knutd.edu.ua/handle/123456789/14355.

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48

Haskett, Kevin Joseph. "Iris Biometric Identification Using Artificial Neural Networks." DigitalCommons@CalPoly, 2018. https://digitalcommons.calpoly.edu/theses/1947.

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A biometric method is a more secure way of personal identification than passwords. This thesis examines the iris as a personal identifier with the use of neural networks as the classifier. A comparison of different feature extraction methods that include the Fourier transform, discrete cosine transform, the eigen analysis method, and the wavelet transform, is performed. The robustness of each method, with respect to distortion and noise, is also studied.

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49

Edara, Praveen Kumar. "Mode Choice Modeling Using Artificial Neural Networks." Thesis, Virginia Tech, 2003. http://hdl.handle.net/10919/9845.

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Artificial intelligence techniques have produced excellent results in many diverse fields of engineering. Techniques such as neural networks and fuzzy systems have found their way into transportation engineering. In recent years, neural networks are being used instead of regression techniques for travel demand forecasting purposes. The basic reason lies in the fact that neural networks are able to capture complex relationships and learn from examples and also able to adapt when new data become available. The primary goal of this thesis is to develop mode choice models using artificial neural n

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Muralidharan, Nair Mithun. "Statistical Leakage Estimation Using Artificial Neural Networks." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1413471610.

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