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Dissertations / Theses on the topic 'Multilayer perceptron (MLP) neural network'

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Published: 3 June 2025

Last updated: 20 July 2025

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1

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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2

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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3

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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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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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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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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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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Gao, Zhenning. "Parallel and Distributed Implementation of A Multilayer Perceptron Neural Network on A Wireless Sensor Network." University of Toledo / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1383764269.

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Midhall, Ruben, and Amir Parmbäck. "Utvärdering av Multilayer Perceptron modeller för underlagsdetektering." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43469.

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Antalet enheter som är uppkopplade till internet, Internet of Things (IoT), ökar hela tiden. År 2035 beräknas det finnas 1000 miljarder Internet of Things-enheter. Samtidigt som antalet enheter ökar, ökar belastningen på internet-nätverken som enheterna är uppkopplade till. Internet of Things-enheterna som finns i vår omgivning samlar in data som beskriver den fysiska tillvaron och skickas till molnet för beräkning. För att hantera belastningen på internet-nätverket flyttas beräkningarna på datan till IoT-enheten, istället för att skicka datan till molnet. Detta kallas för edge computing. IoT-

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Albarakati, Noor. "FAST NEURAL NETWORK ALGORITHM FOR SOLVING CLASSIFICATION TASKS." VCU Scholars Compass, 2012. http://scholarscompass.vcu.edu/etd/2740.

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Classification is one-out-of several applications in the neural network (NN) world. Multilayer perceptron (MLP) is the common neural network architecture which is used for classification tasks. It is famous for its error back propagation (EBP) algorithm, which opened the new way for solving classification problems given a set of empirical data. In the thesis, we performed experiments by using three different NN structures in order to find the best MLP neural network structure for performing the nonlinear classification of multiclass data sets. A developed learning algorithm used here is the ba

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Birkmire, Brian Michael. "Weapon Engagement Zone Maximum Launch Range Approximation using a Multilayer Perceptron." Wright State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=wright1313763379.

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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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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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Manzan, José Ricardo Gonçalves. "Avançada análise do uso de novos vetores-alvo em MLPs de alta performance." Universidade Federal de Uberlândia, 2012. https://repositorio.ufu.br/handle/123456789/14498.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>This work proposes an advanced analysis for MLP performance improvement by adopting new target vectors. Firstly, a mathematical study is done to evaluate the influence of VBOs used as target vectors on MLP training. The VBOs provide the largest possible Euclidean distance between them to improve the training and generalization capability of MLPs. The largest distance inducement between points from output space leads to direct correspondence on pattern classification improvement. The various types of target vectors such as VBNs, VBC

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Ignatavičienė, Ieva. "Tiesioginio sklidimo neuroninių tinklų sistemų lyginamoji analizė." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2012. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2012~D_20120801_133809-03141.

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Pagrindinis darbo tikslas – atlikti kelių tiesioginio sklidimo neuroninių tinklų sistemų lyginamąją analizę siekiant įvertinti jų funkcionalumą. Šiame darbe apžvelgiama: biologinio ir dirbtinio neuronų modeliai, neuroninių tinklų klasifikacija pagal jungimo konstrukciją (tiesioginio sklidimo ir rekurentiniai neuroniniai tinklai), dirbtinių neuroninių tinklų mokymo strategijos (mokymas su mokytoju, mokymas be mokytojo, hibridinis mokymas). Analizuojami pagrindiniai tiesioginio sklidimo neuroninių tinklų metodai: vienasluoksnis perceptronas, daugiasluoksnis perceptronas realizuotas „klaidos skle

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Djupfeldt, Petter. "Dr. Polopoly - IntelligentSystem Monitoring : An Experimental and Comparative Study ofMultilayer Perceptrons and Random Forests ForError Diagnosis In A Network of Servers." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191557.

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This thesis explores the potential of using machine learning to superviseand diagnose a computer system by comparing how Multilayer Perceptron(MLP) and Random Forest (RF) perform at this task in a controlledenvironment. The base of comparison is primarily how accurate theyare in their predictions, but some thought is given to how cost effectivethey are regarding time. The specific system used is a content management system (CMS)called Polopoly. The thesis details how training samples were collectedby inserting Java proxys into the Polopoly system in order to time theinter-server method calls.

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Tamas, Wani Théo. "Prévision statistique de la qualité de l’air et d’épisodes de pollution atmosphérique en Corse." Thesis, Corte, 2015. http://www.theses.fr/2015CORT0010/document.

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L’objectif de ces travaux de doctorat est de développer un modèle prédictif capable de prévoir correctement les concentrations en polluants du jour pour le lendemain en Corse. Nous nous sommes intéressés aux PM10 et à l’ozone, les deux polluants les plus problématiques sur l’île. Le modèle devait correspondre aux contraintes d’un usage opérationnel au sein d’une petite structure, comme Qualitair Corse, l’association locale de surveillance de la qualité de l’air.La prévision a été réalisée à l’aide de réseaux de neurones artificiels. Ces modèles statistiques offrent une grande précision tout en

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Rönnholm, Niklas. "A study of limitations and performance in scalable hosting using mobile devices." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-224646.

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At present day, distributed computing is a widely used technique, where volunteers support different computing power needs organizations might have. This thesis sought to benchmark distributed computing performance limited to mobile device support since this type of support is seldom done with mobile devices. This thesis proposes two approaches to harnessing computational power and infrastructure of a group of mobile devices. The problems used for benchmarking are small instances of deep learning training. One requirement posed by the mobile devices’ non-static nature was that this should be p

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Silva, Aldemário Alves da. "Desenvolvimento e aplicação de Heurística para calcular pesos e bias iniciais para o “Back-Propagation” treinar Rede Neural Perceptron Multicamadas." Universidade Federal Rural do Semi-Árido, 2017. http://bdtd.ufersa.edu.br:80/tede/handle/tede/806.

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Submitted by Lara Oliveira (lara@ufersa.edu.br) on 2017-09-08T22:30:39Z No. of bitstreams: 1 AldemárioAS_DISSERT.pdf: 18856416 bytes, checksum: dcd37bbe9d111ef051c4d27c3481a41f (MD5)<br>Approved for entry into archive by Vanessa Christiane (referencia@ufersa.edu.br) on 2017-09-11T16:27:51Z (GMT) No. of bitstreams: 1 AldemárioAS_DISSERT.pdf: 18856416 bytes, checksum: dcd37bbe9d111ef051c4d27c3481a41f (MD5)<br>Approved for entry into archive by Vanessa Christiane (referencia@ufersa.edu.br) on 2017-09-11T16:28:25Z (GMT) No. of bitstreams: 1 AldemárioAS_DISSERT.pdf: 18856416 bytes, checksum: dcd37b

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Wilgenbus, Erich Feodor. "The file fragment classification problem : a combined neural network and linear programming discriminant model approach / Erich Feodor Wilgenbus." Thesis, North-West University, 2013. http://hdl.handle.net/10394/10215.

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The increased use of digital media to store legal, as well as illegal data, has created the need for specialized tools that can monitor, control and even recover this data. An important task in computer forensics and security is to identify the true le type to which a computer le or computer le fragment belongs. File type identi cation is traditionally done by means of metadata, such as le extensions and le header and footer signatures. As a result, traditional metadata-based le object type identi cation techniques work well in cases where the required metadata is available and unaltered

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Santos, Rosiane Correia. "LearnInPlanner: uma abordagem de aprendizado supervisionado com redes neurais para solução de problemas de planejamento clássico." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/100/100131/tde-25012014-115621/.

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A busca progressiva no espaço de estados é uma das abordagens mais populares de Planejamento Automatizado. O desempenho dos algoritmos de busca progressiva é influenciado pela heurística independente de domínio utilizada para guiá-lo. Nesse contexto, o foco do presente trabalho consiste em investigar técnicas de aprendizado de máquina supervisionadas que possibilitaram agregar à heurística do plano relaxado, comumente utilizada em abordagens atuais de planejamento, informações sobre o domínio em questão que viessem a ser úteis ao algoritmo de busca. Essas informações foram representadas por me

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Tinós, Renato. "Detecção e diagnóstico de falhas em robôs manipuladores via redes neurais artificiais." Universidade de São Paulo, 1999. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-04022002-162950/.

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Neste trabalho, um novo enfoque para detecção e diagnóstico de falhas (DDF) em robôs manipuladores é apresentado. Um robô com falhas pode causar sérios danos e pode colocar em risco o pessoal presente no ambiente de trabalho. Geralmente, os pesquisadores têm proposto esquemas de DDF baseados no modelo matemático do sistema. Contudo, erros de modelagem podem ocultar os efeitos das falhas e podem ser uma fonte de alarmes falsos. Aqui, duas redes neurais artificiais são utilizadas em um sistema de DDF para robôs manipuladores. Um perceptron multicamadas treinado por retropropagação do erro é usa

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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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Křepský, Jan. "Rekurentní neuronové sítě v počítačovém vidění." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-237029.

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The thesis concentrates on using recurrent neural networks in computer vision. The theoretical part describes the basic knowledge about artificial neural networks with focus on a recurrent architecture. There are presented some of possible applications of the recurrent neural networks which could be used for a solution of real problems. The practical part concentrates on face recognition from an image sequence using the Elman simple recurrent network. For training there are used the backpropagation and backpropagation through time algorithms.

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Kostka, Filip. "Umělá neuronová síť pro modelování polí uvnitř automobilu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220578.

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The project deals with artificial neural networks. After designing and debugging the test data set and the training sample set, we created a multilayer perceptron network in the Neural NetworkToolbox (NNT) of Matlab. When creating networks, we used different training algorithms and algorithms improving the generalization of the network. When creating a radial basis network, we did not use the NNT, but a specific source code in Matlab was written. Functionality of neural networks was tested on simple training and testing patterns. Realistic training data were obtained by the simulation of twelv

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Sun, Zhibin. "Application of artificial neural networks in early detection of Mastitis from improved data collected on-line by robotic milking stations." Lincoln University, 2008. http://hdl.handle.net/10182/665.

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Two types of artificial neural networks, Multilayer Perceptron (MLP) and Self-organizing Feature Map (SOM), were employed to detect mastitis for robotic milking stations using the preprocessed data relating to the electrical conductivity and milk yield. The SOM was developed to classify the health status into three categories: healthy, moderately ill and severely ill. The clustering results were successfully evaluated and validated by using statistical techniques such as K-means clustering, ANOVA and Least Significant Difference. The result shows that the SOM could be used in the robotic milki

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BRANDL, ALBERTO. "Techniques for effective virtual sensor development and implementation with application to air data systems." Doctoral thesis, Politecnico di Torino, 2020. http://hdl.handle.net/11583/2842493.

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Richter, Jan. "Využití metod umělé inteligence pro simulaci a identifikaci dat v oblasti proudění." Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-391879.

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It is possible to simulate an airflow by additives to shoot images and records of such flowing. Additives can be in the form of particles or continuous filaments. A computer evaluation of such data differs depending on the kind of visualization method. This thesis deals with a number of different approaches to determine the airjet shape and airflow velocity in airflow images and records. Exact procedures area sed for these purposes as well as neural networks and genetic algorithms.

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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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Narmack, Kirilll. "Dynamic Speed Adaptation for Curves using Machine Learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233545.

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The vehicles of tomorrow will be more sophisticated, intelligent and safe than the vehicles of today. The future is leaning towards fully autonomous vehicles. This degree project provides a data driven solution for a speed adaptation system that can be used to compute a vehicle speed for curves, suitable for the underlying driving style of the driver, road properties and weather conditions. A speed adaptation system for curves aims to compute a vehicle speed suitable for curves that can be used in Advanced Driver Assistance Systems (ADAS) or in Autonomous Driving (AD) applications. This degree

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Козаченко, А. П. "Інформаційне та програмне забезпечення системи інтелектуального аналізу енергоспоживання будівель". Master's thesis, Сумський державний університет, 2018. http://essuir.sumdu.edu.ua/handle/123456789/72073.

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Розроблено алгоритм та програмне забезпечення інтелектуальної системи класифікації будівель за рівнем енергоспоживання на базі комплексної оцінки енерговитрат в зимовий та літній період. В роботі проведено оптимізація параметрів стандартного алгоритму навчання нейромереж зворотного розповсюдження помилки, що дозволило підвищити ефективність сформованого нейромережевого класифікатору. Розроблений алгоритм реалізовано у формі m-сценаріїв середовища для наукових і інженерних розрахунків MATLAB 6.5.

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Leonavičius, Romas. "Melizmų sintezė dirbtinių neuronų tinklais." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2007. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2006~D_20070112_145929-44906.

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Modern methods of speech synthesis are not suitable for restoration of song signals due to lack of vitality and intonation in the resulted sounds. The aim of presented work is to synthesize melismas met in Lithuanian folk songs, by applying Artificial Neural Networks. An analytical survey of rather a widespread literature is presented. First classification and comprehensive discussion of melismas are given. The theory of dynamic systems which will make the basis for studying melismas is presented and finally the relationship for modeling a melisma with nonlinear and dynamic systems is outlined

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Buhot, Arnaud. "Etude de propriétés d'apprentissage supervisé et non supervisé par des méthodes de Physique Statistique." Phd thesis, Université Joseph Fourier (Grenoble), 1999. http://tel.archives-ouvertes.fr/tel-00001642.

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L'objet de cette thèse est l'étude de diverses propriétés d'apprentissage à partir d'exemples par des méthodes de Physique Statistique, notamment, par la méthode des répliques. Des tâches supervisées, correspondant à la classification binaire de données, ainsi que des tâches non supervisées, comme l'estimation paramétrique d'une densité de probabilité, sont considérées. Dans la première partie, une approche variationnelle permet de déterminer la performance de l'apprentissage optimal d'une direction d'anisotropie, et de déduire une fonction de coût permettant d'obtenir ces performances optimal

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Kumar, Rajan. "A Neural Network Approach To Rotorcraft Parameter Estimation." Thesis, 2007. https://etd.iisc.ac.in/handle/2005/549.

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The present work focuses on the system identification method of aerodynamic parameter estimation which is used to calculate the stability and control derivatives required for aircraft flight mechanics. A new rotorcraft parameter estimation technique is proposed which uses a type of artificial neural network (ANN) called radial basis function network (RBFN). Rotorcraft parameter estimation using ANN is an unexplored research topic and the earlier works in this area have used the output error, equation error and filter error methods which are conventional parameter estimation methods. However, t

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Kumar, Rajan. "A Neural Network Approach To Rotorcraft Parameter Estimation." Thesis, 2007. http://hdl.handle.net/2005/549.

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The present work focuses on the system identification method of aerodynamic parameter estimation which is used to calculate the stability and control derivatives required for aircraft flight mechanics. A new rotorcraft parameter estimation technique is proposed which uses a type of artificial neural network (ANN) called radial basis function network (RBFN). Rotorcraft parameter estimation using ANN is an unexplored research topic and the earlier works in this area have used the output error, equation error and filter error methods which are conventional parameter estimation methods. However, t

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Silva, Daniel Alexandre Felício da. "Multilayer perceptron modelling of industrial cultivation processes for DNA vaccine production control and optimization." Doctoral thesis, 2013. http://hdl.handle.net/10400.14/16698.

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Bioinformatics is one of the emerging fields in Computer Sciences with an increasingly more impactful role, in a symbiotic-like association with Biology and Bioprocesses, aiding in the knowledge of complex mechanisms and elements in both these fields of knowledge. The permanent and exponential development of equipments that allow large-scale data acquisition, has set-in-motion the need to create methodologies to store and analyze that same data, in a manner that researchers can extract its meaning, with a high degree of confidence and precision, in a viable time-frame, and therefore help them

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Dubey, Abhishek. "Multimodal Deep Learning for Multi-Label Classification and Ranking Problems." Thesis, 2015. http://etd.iisc.ac.in/handle/2005/3681.

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In recent years, deep neural network models have shown to outperform many state of the art algorithms. The reason for this is, unsupervised pretraining with multi-layered deep neural networks have shown to learn better features, which further improves many supervised tasks. These models not only automate the feature extraction process but also provide with robust features for various machine learning tasks. But the unsupervised pretraining and feature extraction using multi-layered networks are restricted only to the input features and not to the output. The performance of many supervised lear

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Dubey, Abhishek. "Multimodal Deep Learning for Multi-Label Classification and Ranking Problems." Thesis, 2015. http://etd.iisc.ernet.in/2005/3681.

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In recent years, deep neural network models have shown to outperform many state of the art algorithms. The reason for this is, unsupervised pretraining with multi-layered deep neural networks have shown to learn better features, which further improves many supervised tasks. These models not only automate the feature extraction process but also provide with robust features for various machine learning tasks. But the unsupervised pretraining and feature extraction using multi-layered networks are restricted only to the input features and not to the output. The performance of many supervised lear

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Liang, Ching-Hau, and 梁鈞皓. "Reconfigurable Neural Network Architectures Based on Multilayer Perceptron." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/9jcr7b.

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碩士<br>逢甲大學<br>資訊工程所<br>90<br>Field Programmable Gate Array (FPGA) is an emerging hardware device recently. It make the products that produced by hardware designer enter the market quickly. And neural network is an important algorithm which recognition task needs. It is usually simulated by software, but the speed is not enough to satisfy the recognition task of real time. So, it is the best way to accelerate the neural network computing by implement with hardware. However, it lacks the resilience if implemented by ASIC. Therefore, the FPGA, which could adjust with different requirements,. Ex:

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Weng, Zi-Jie, and 翁梓捷. "Using Multilayer Perceptron Neural Network to Assess the Critical Factors of Traffic Accidents." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/4q4hqh.

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碩士<br>國立高雄第一科技大學<br>資訊管理系碩士班<br>106<br>In accordance with a report issued by the Ministry of Health and Welfare in 2017, it stated that death resulted from accident injury was the sixth fatal factor in 2016.Consequently, it is crucial to promote a better traffic prevention so as to avoid any possible traffic accidents. Nonetheless, due to the changing features of environment, drivers behaviors and others, the types of traffic accidents are diversified. This study is based on the data of traffic accidents in Taoyuan City in the government-opened data and the application of the data mining techn

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Chen, Ching-Chang, and 陳清泉. "Applying the method of multilayer perceptron neural network on high confused Mandarin vowel recognition." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/34273138390578821085.

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碩士<br>國立中興大學<br>統計學研究所<br>105<br>This thesis is mainly to apply the method of multilayer perceptron on two types of high confused Mandarin vowel recognition like <ㄣ、ㄥ>、<ㄛ、ㄨㄛ>、<ㄥ、ㄨㄥ> and so on.First, we would record the voices of twenty different speakers, and preprocess the voice signal like Digiting, Frame Blocking, Windowing and so on. Then MFCC are taken as the features of the voice signal, and the features of training data would be served as the input data to train the model. After training, input the test data and get the output of multilayer perceptron as the recognition rate of vowel. W

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Carrelli, David John. "Utilising Local Model Neural Network Jacobian Information in Neurocontrol." Thesis, 2006. http://hdl.handle.net/10539/1815.

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Student Number : 8315331 - MSc dissertation - School of Electrical and Information Engineering - Faculty of Engineering and the Built Environment<br>In this dissertation an efficient algorithm to calculate the differential of the network output with respect to its inputs is derived for axis orthogonal Local Model (LMN) and Radial Basis Function (RBF) Networks. A new recursive Singular Value Decomposition (SVD) adaptation algorithm, which attempts to circumvent many of the problems found in existing recursive adaptation algorithms, is also derived. Code listings and simulations are presented

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Carvalho, João Gabriel Marques. "Electricity consumption forecast model for the DEEC based on machine learning tools." Master's thesis, 2020. http://hdl.handle.net/10316/90148.

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Dissertação de Mestrado Integrado em Engenharia Electrotécnica e de Computadores apresentada à Faculdade de Ciências e Tecnologia<br>Nesta tese apresentaremos o trabalho sobre a criação de uma rede neuronal de aprendizagem automática, capaz de realizar previsões energéticas. Com o aumento do consumo energético, devem desenvolvidas ferramentas capazes de prever o consumo. Esta necessidade levou à pesquisa deste tema.Procura-se explicar a história da aprendizagem automática, o que é a aprendizagem automática e como é que esta funciona. Também se procura explicar os seus antecedentes matemáticos,

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Oba, Pius Nwachukwu. "Quality analysis modelling for development of a process controller in resistance spot welding using neural networks techniques." Thesis, 2006. http://hdl.handle.net/10539/1676.

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Student Number : 9811923K - PhD thesis - School of Mechanical Engineering - Faculty of Engineering and the Built Environment<br>Methods are presented for obtaining models used for predicting welded sample resistance and effective weld current (RMS) for desired weld diameter (weld quality) in the resistance spot welding process. These models were used to design predictive controllers for the welding process. A suitable process model forms an important step in the development and design of process controllers for achieving good weld quality with good reproducibility. Effective current, dynam

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Teixeira, Rafael Gonçalves. "Energy disaggregation using Machine Learning." Master's thesis, 2021. http://hdl.handle.net/10773/33657.

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Nowadays, we are surrounded by electric appliances. Either at home by the washing machine, kettle, or oven, or work by the computer, cellphone, or printer. Such devices help us daily, but their popularization increased the energy consumption to concerning values. In an attempt to reduce energy consumption, governments started enforcing policies regarding energy education to teach homeowners how to reduce energy wastage on the demand side. One of those policies was the deployment of smart meters, which allow the consumer to know how much energy is being consumed at any given time through

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Silvestre, Martinho de Matos. "Three-stage ensemble model : reinforce predictive capacity without compromising interpretability." Master's thesis, 2019. http://hdl.handle.net/10362/71588.

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Thesis proposal presented as partial requirement for obtaining the Master’s degree in Statistics and Information Management, with specialization in Risk Analysis and Management<br>Over the last decade, several banks have developed models to quantify credit risk. In addition to the monitoring of the credit portfolio, these models also help deciding the acceptance of new contracts, assess customers profitability and define pricing strategy. The objective of this paper is to improve the approach in credit risk modeling, namely in scoring models to predict default events. To this end, we propose t

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Sousa, Martim Afonso Gouveia. "Previsão de vendas de peças de substituição para otimização da gestão de stock." Master's thesis, 2021. http://hdl.handle.net/10773/32749.

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Este projeto tem como intuito prever o número de vendas de peças de substituição, associadas a equipamentos de termotecnologia, das próximas três semanas para a empresa Bosch Termotecnologia-Aveiro. Desta forma, a Bosch pode otimizar o planeamento de produção e stocks garantindo a satisfação do cliente final. A nossa abordagem ao problema consiste no estudo das séries temporais de vendas destas peças de substituição, construindo modelos matemáticos capazes de captar os padrões existentes nos dados. Os modelos utilizados cobrem um largo espetro de metodologias, por forma a acomodar dife

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Василенко, Дмитро Олексійович. "Конструктивний синтез планарних антен природними алгоритмами оптимізації". Doctoral thesis, 2010. https://ela.kpi.ua/handle/123456789/641.

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