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1

Kotta, Anwesh. "Condition Monitoring : Using Computational intelligence methods." Master's thesis, Universitätsbibliothek Chemnitz, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-187100.

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Machine tool components are widely used in many industrial applications. In accordance with their usage, a reliable health monitoring system is necessary to detect defects in these components in order monitor machinery performance and avoid malfunction. Even though several techniques have been reported for fault detection and diagnosis, it is a challenging task to implement a condition monitoring system in real world applications due to their complexity in structure and noisy operating environment. The primary objective of this thesis is to develop novel intelligent algorithms for a reliable f
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Eminoglu, Ilyas. "Computational intelligence methods : generic interpretations, optimisation and application." Thesis, University of Sheffield, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.289703.

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Ekong, Udeme Essien. "Development of computational intelligence methods to deal with classification problems." Thesis, King's College London (University of London), 2016. https://kclpure.kcl.ac.uk/portal/en/theses/development-of-computational-intelligence-methods-to-deal-with-classi-cation-problems(0f04e932-0e3d-4309-a21f-1e2f6df6d29d).html.

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In the thesis presented here, variations of two very prominent machine learning techniques, the Neural Network (NN) and Support Vector Machine (SVM) are used in an attempt to solve two classification problems. Classification involves the assignment of an unknown object into a pre-determined group which consists of a set of preclassified objects with similar features to that unknown object. The main theme of the research conducted in this thesis involves investigation into existing and proposed classifier architectures to improve the classification performance for certain research problems. The
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West, Graeme Michael. "Computational intelligence methods for power system protection design and decision support." Thesis, University of Strathclyde, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.400311.

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Green, Robert C. II. "Novel Computational Methods for the Reliability Evaluation of Composite Power Systems using Computational Intelligence and High Performance Computing Techniques." University of Toledo / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1338894641.

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6

Devergne, Timothée. "Machine learning methods for computational studies in origins of life." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS376.

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La chimie prébiotique consiste en l’étude des réactions chimiques aux origines de la vie sur Terre. C’est un très vaste sujet qui mobilise plusieurs domaines scientifiques dont la physique numérique. En effet, des simulations de dynamiques moléculaire de haute précision peuvent être menées pour tester l’influence de différents environnements plausibles sur la synthèse de molécules : ce composant a-t-il pu apparaître dans le milieu interstellaire ? Sa formation est-elle favorisée par la présence de surfaces minérales ? Elles peuvent aussi être utilisées pour identifier des intermédiaires réacti
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Abdullah, Rudwan Ali Abolgasim. "Intelligent methods for complex systems control engineering." Thesis, University of Stirling, 2007. http://hdl.handle.net/1893/257.

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This thesis proposes an intelligent multiple-controller framework for complex systems that incorporates a fuzzy logic based switching and tuning supervisor along with a neural network based generalized learning model (GLM). The framework is designed for adaptive control of both Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) complex systems. The proposed methodology provides the designer with an automated choice of using either: a conventional Proportional-Integral-Derivative (PID) controller, or a PID structure based (simultaneous) Pole and Zero Placement controller. The
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JIMENEZ, JUAN DARIO TIMARAN. "METHODS BASED ON COMPUTATIONAL INTELLIGENCE TECHNIQUES FOR LOCALIZATION OF FIREARMS PROJECTILES INSERTED INTO THE HUMAN BODY, BY HIGH SENSITIVITY MAGNETIC MEASUREMENTS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=32028@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE EXCELENCIA ACADEMICA<br>Um dos casos clínicos mais frequentes na sociedade moderna envolve a localização e extração de projéteis de armas de fogo, que normalmente são feitos de chumbo, um material não ferromagnético. O desenvolvimento de uma técnica que possibilite a localização precisa destes auxiliará o procedimento de remoção cirúrgica, tendo vasta relevância e impactando diretamente no aumento da taxa de sobrevivência de pessoas feridas. Dessa forma, esta disser
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Groves, Adrian R. "Bayesian learning methods for modelling functional MRI." Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:fe46e696-a1a6-4a9d-9dfe-861b05b1ed33.

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Bayesian learning methods are the basis of many powerful analysis techniques in neuroimaging, permitting probabilistic inference on hierarchical, generative models of data. This thesis primarily develops Bayesian analysis techniques for magnetic resonance imaging (MRI), which is a noninvasive neuroimaging tool for probing function, perfusion, and structure in the human brain. The first part of this work fits nonlinear biophysical models to multimodal functional MRI data within a variational Bayes framework. Simultaneously-acquired multimodal data contains mixtures of different signals and ther
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Ferreira, Junior Valnir, and N/A. "Improvements to Clause Weighting Local Search for Propositional Satisfiability." Griffith University. Institute for Integrated and Intelligent Systems, 2007. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20070823.123257.

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The propositional satisfiability (SAT) problem is of considerable theoretical and practical relevance to the artificial intelligence (AI) community and has been used to model many pervasive AI tasks such as default reasoning, diagnosis, planning, image interpretation, and constraint satisfaction. Computational methods for SAT have historically fallen into two broad categories: complete search and local search. Within the local search category, clause weighting methods are amongst the best alternatives for SAT, becoming particularly attractive on problems where a complete search is impractical
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Ferreira, Junior Valnir. "Improvements to Clause Weighting Local Search for Propositional Satisfiability." Thesis, Griffith University, 2007. http://hdl.handle.net/10072/365857.

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The propositional satisfiability (SAT) problem is of considerable theoretical and practical relevance to the artificial intelligence (AI) community and has been used to model many pervasive AI tasks such as default reasoning, diagnosis, planning, image interpretation, and constraint satisfaction. Computational methods for SAT have historically fallen into two broad categories: complete search and local search. Within the local search category, clause weighting methods are amongst the best alternatives for SAT, becoming particularly attractive on problems where a complete search is impractical
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Kohler, Daniel G. "STUDY OF STATISTICAL AND COMPUTATIONAL INTELLIGENCE METHODS OF DETECTING TEMPORAL SIGNATURE OF FOREST FIRE HEAT PLUME FROM SINGLE-BAND GROUND-BASED INFRARED VIDEO." DigitalCommons@CalPoly, 2012. https://digitalcommons.calpoly.edu/theses/796.

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This thesis will analyze video from land-based, cooled mid-wave infrared cameras to identify temporal features indicative of a heat plume from a forest fire. Desirable features and methods will show an ability to distinguish between heat plume movement and other movements, such as foliage, vehicles, humans, and birds in flight. Features will be constructed primarily using combinations of statistics and principal component analysis (PCA) with intent to detect key characteristics of fire and heat plume: persistence and growth. Several classification systems will combine and filter the features i
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Felske, Sven [Verfasser]. "Einsatz von Computational-Intelligence-Methoden zur Bestimmung von Adsorptionsisothermen aus Chromatogrammen / Sven Felske." Aachen : Shaker, 2006. http://d-nb.info/1166513351/34.

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Eleuterio, Marco Antonio. "AMANDA : a computational method for mediating asynchronous group discussions." Compiègne, 2002. http://www.theses.fr/2002COMP1400.

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Cette thèse traite de la communication assistée par ordinateur. Nous proposons AMANDA, une méthode algorithmique pour la médiation de discussions de groupe à distance destinée à l'articulation d'une discussion collective sans effort humain de coordination. La méthode consiste à lancer un ensemble de questions parmi un groupe de participants et ensuite à relancer leurs réponses et arguments en des cycles de discussions successifs. Tout au long de la discussion, des mécanismes intelligents identifient les interactions potentielles entre les participants du débat et proposent des nouvelles intera
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Saha, Deba Pratim. "A Study of Methods in Computational Psychophysiology for Incorporating Implicit Affective Feedback in Intelligent Environments." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/84469.

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Technological advancements in sensor miniaturization, processing power and faster networks has broadened the scope of our contemporary compute-infrastructure to an extent that Context-Aware Intelligent Environment (CAIE)--physical spaces with computing systems embedded in it--are increasingly commonplace. With the widespread adoption of intelligent personal agents proliferating as close to us as our living rooms, there is a need to rethink the human-computer interface to accommodate some of their inherent properties such as multiple focus of interaction with a dynamic set of devices and
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Feydy, Jean. "Analyse de données géométriques, au delà des convolutions." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASN017.

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Analyse de données géométriques, au delà des convolutionsPour modéliser des interactions entre points, une méthode simple est de se reposer sur des sommes pondérées communément appelées "convolutions". Au cours de la dernière décennie, cette opération est devenue la brique de construction essentielle à la révolution du "deep learning". Le produit de convolution est, toutefois, loin d'être l'alpha et l'oméga des mathématiques appliquées.Pour permettre aux chercheurs d'explorer de nouvelles directions, nous présentons des implémentations robustes et efficaces de trois opérations souvent sous-est
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Patzwahl, Steffen [Verfasser]. "Einsatz von Methoden der Computational Intelligence auf Mikrocontrollersystemen zur Realisierung von Prozessführungssystemen am Beispiel der anaeroben Biogasfermentation / Steffen Patzwahl." Aachen : Shaker, 2005. http://d-nb.info/1181614406/34.

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18

Huntsinger, Richard A. "Evaluating Forecasting Performance in the Context of Process-Level Decisions: Methods, Computation Platform, and Studies in Residential Electricity Demand Estimation." Research Showcase @ CMU, 2017. http://repository.cmu.edu/dissertations/898.

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This dissertation explores how decisions about the forecasting process can affect the evaluation of forecasting performance, in general and in the domain of residential electricity demand estimation. Decisions of interest include those around data sourcing, sampling, clustering, temporal magnification, algorithm selection, testing approach, evaluation metrics, and others. Models of the forecasting process and analysis methods are formulated in terms of a three-tier decision taxonomy, by which decision effects are exposed through systematic enumeration of the techniques resulting from those dec
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Mbangeni, Litha. "Development of methods for parallel computation of the solution of the problem for optimal control." Thesis, Cape Peninsula University of Technology, 2010. http://hdl.handle.net/20.500.11838/1110.

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Thesis (MTech(Electrical Engineering))--Cape Peninsula University of Technology, 2010<br>Optimal control of fermentation processes is necessary for better behaviour of the process in order to achieve maximum production of product and biomass. The problem for optimal control is a very complex nonlinear, dynamic problem requiring long time for calculation Application of decomposition-coordinating methods for the solution of this type of problems simplifies the solution if it is implemented in a parallel way in a cluster of computers. Parallel computing can reduce tremendously the time of ca
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Angelsmark, Ola. "Constructing Algorithms for Constraint Satisfaction and Related Problems : Methods and Applications." Doctoral thesis, Linköping : Univ, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-3836.

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Lagerkvist, Love. "Computation as Strange Material : Excursions into Critical Accidents." Thesis, Malmö universitet, Institutionen för konst, kultur och kommunikation (K3), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43639.

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Waking up in a world where everyone carries a miniature supercomputer, interaction designers find themselves in their forerunners dreams. Faced with the reality of planetary-scale we have to confront the task of articulating approaches responsive this accidental ubiquity of computation. This thesis attempts such a formulation by defining computation as a strange material, a plasticity shaped equally by its technical properties and the mode of production by which is its continuously re-produced. The definition is applied through a methodology of excursions — participatory explorations into two
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Silva, Junior Marco Aurélio Jucá da. "Interrogação de sensores a fibra óptica através de métodos computacionais." Universidade Federal de Juiz de Fora (UFJF), 2018. https://repositorio.ufjf.br/jspui/handle/ufjf/8002.

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Submitted by Geandra Rodrigues (geandrar@gmail.com) on 2018-11-12T16:13:04Z No. of bitstreams: 1 marcoaureliojucadasilvajunior.pdf: 2424952 bytes, checksum: 8217d429e23695cdfd64e035686f02db (MD5)<br>Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2018-11-23T11:04:13Z (GMT) No. of bitstreams: 1 marcoaureliojucadasilvajunior.pdf: 2424952 bytes, checksum: 8217d429e23695cdfd64e035686f02db (MD5)<br>Made available in DSpace on 2018-11-23T11:04:13Z (GMT). No. of bitstreams: 1 marcoaureliojucadasilvajunior.pdf: 2424952 bytes, checksum: 8217d429e23695cdfd64e035686f
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Pinto, Marcio Augusto Sampaio 1977. "Método de otimização assitido para comparação entre poços convencionais e inteligentes considerando incertezas." [s.n.], 2013. http://repositorio.unicamp.br/jspui/handle/REPOSIP/263725.

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Orientador: Denis José Schiozer<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica e Instituto de Geociências<br>Made available in DSpace on 2018-08-24T00:34:10Z (GMT). No. of bitstreams: 1 Pinto_MarcioAugustoSampaio_D.pdf: 5097853 bytes, checksum: bc8b7f6300987de2beb9a57c26ad806a (MD5) Previous issue date: 2013<br>Resumo: Neste trabalho, um método de otimização assistido é proposto para estabelecer uma comparação refinada entre poços convencionais e inteligentes, considerando incertezas geológicas e econômicas. Para isto é apresentada uma metodologia d
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Pires, Michael Maio. "American Option Pricing Using Computational Intelligence Methods." Thesis, 2006. http://hdl.handle.net/10539/268.

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Master of Science in Engineering - Engineering<br>An option is the right to buy or sell an underlying asset at a future date by fixing the price now. The field of option pricing produces a challenge because of the complexity with pricing American styled options which cannot be done by the Black-Scholes equations. Neural Networks and Machine Learning techniques are predictors based on past data and it is intuitive to believe that they can model American options as they are non-linear instruments. Call option data on the South African All Share Index (ALSI) was used for testing of the techniqu
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Jhou, Hou-Yu, and 周厚宇. "Image Haze Removal Using Computational Intelligence Methods." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/22352544333454728309.

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碩士<br>國立勤益科技大學<br>資訊工程系<br>102<br>The image quality will be reduced with the light attenuation by atmospheric particles when taking a photograph outdoors, especially in the environment with haze. Because the hazy images lose a lot of information, the image recognition systems cannot recognize the target in the image. In order to solve the problem of the image quality attenuation, there are two image dehazing methods proposed in this paper. To use the proposed fuzzy inference system is able to estimate the attenuation condition of the light. For the problem of the halo artifacts, this paper com
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Betechuoh, Brain Leke. "Optimal selection of stocks using computational intelligence methods." Thesis, 2006. http://hdl.handle.net/10539/165.

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Master of Science in Engineering - Engineering<br>Various methods, mostly statistical in nature have been introduced for stock market modelling and prediction. These methods are, however, complex and difficult to manipulate. Computational intelligence facilitates this approach of predicting stocks due to its ability to accurately and intuitively learn complex patterns and characterise these patterns as simple equations. In this research, a methodology that uses neural networks and Bayesian framework to model stocks is developed. The NASDAQ all-share index was used as test data. A methodology
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Mishra, Sanjib. "Short Term Load Forecasting Using Computational Intelligence Methods." Thesis, 2009. http://ethesis.nitrkl.ac.in/1412/1/FINAL_THESIS.pdf.

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Load forecasting is very essential to the operation of electricity companies. It enhances the energy-efficient and reliable operation of a power system. This dissertation focuses on study of short term load forecasting using different types of computational intelligence methods. It uses evolutionary algorithms (i.e. Genetic Algorithm, Particle Swarm Optimization, Artificial Immune System), neural networks (i.e. MLPNN, RBFNN, FLANN, ADALIN, MFLNN, WNN, Recurrent NN, Wilcoxon NN), and fuzzy systems (i.e. ANFIS). The developed methods give load forecasts of one hour upto 24 hours in advance. The
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Chen, Yingying. "Novel computational methods for wind farm integrated power systems using computational intelligence and advanced computing techinques." Thesis, 2014. http://hdl.handle.net/1959.13/1045384.

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Research Doctorate - Doctor of Philosophy (PhD)<br>Over the last few decades, due to the environmental concerns and the increase of energy demand, wind power has strongly penetrated the electricity power generation industry. Wind power is variable, uncertain, and intermittent. The system planning, operation and control associated with wind farms are therefore considerably different from conventional power systems. Thus, the integration of wind farms has become the biggest challenges for system operators. The research described in this thesis focuses on the novel computational methods used to a
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Vladutu, Liviu-Mihai. "Computational intelligence methods on biomedical signal analysis and data mining in medical records." Thesis, 2004. http://nemertes.lis.upatras.gr/jspui/handle/10889/1549.

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This thesis is centered around the development and application of computationally effective solutions based on artificial neural networks (ANN) for biomedical signal analysis and data mining in medical records. The ultimate goal of this work in the field of Biomedical Engineering is to provide the clinician with the best possible information needed to make an accurate diagnosis (in our case of myocardial ischemia) and to propose advanced mathematical models for recovering the complex dependencies between the variables of a physical process from a set of perturbed observations. After describ
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Dragomir, Andrei. "Discovery of gene interactions in regulatory networks using genomic data mining and computational intelligence methods." Thesis, 2006. http://nemertes.lis.upatras.gr/jspui/handle/10889/1176.

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The advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to an enormous progress in life sciences. Among the most important innovations is the microarray technology. It allows to quantify the expression of thousands of genes simultaneously by measuring the hybridization from a tissue of interest to probes on a small glass or plastic slide. Before launching into microarray research it is important to recall that the characteristics of this data include a fair amount of noise and an atypical dimensionality (which makes difficult the use of classic s
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"Computational Methods for Knowledge Integration in the Analysis of Large-scale Biological Networks." Doctoral diss., 2012. http://hdl.handle.net/2286/R.I.15204.

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abstract: As we migrate into an era of personalized medicine, understanding how bio-molecules interact with one another to form cellular systems is one of the key focus areas of systems biology. Several challenges such as the dynamic nature of cellular systems, uncertainty due to environmental influences, and the heterogeneity between individual patients render this a difficult task. In the last decade, several algorithms have been proposed to elucidate cellular systems from data, resulting in numerous data-driven hypotheses. However, due to the large number of variables involved in the proces
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Lee, Chih-Yuan, and 李誌原. "Forecasting the Revenue of Mobile Telecommunications Operators in Taiwan: A Comparison between Time Series and Computational Intelligence Methods." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/f23f46.

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碩士<br>輔仁大學<br>統計資訊學系應用統計碩士在職專班<br>106<br>The mobile telecommunications market in Taiwan is vigorous after opening up to private enterprises. The mobile telecommunications industry is a franchise industry and currently there are five telecommunications licensees. The competitive environment resulted in a decrease of operating revenue, which is a significant indicator of the operational strategies of mobile telecommunications operators, the management policies of government agencies, and investment decisions of investors. Accurately forecasting revenue is a very remarkable research topic. Howeve
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Mpanza, Lindokuhle Justice. "A rough set approach to bushings fault detection." Thesis, 2012. http://hdl.handle.net/10210/4955.

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M. Ing.<br>Fault detection tools have gained popularity in recent years due to the increasing need for reliable and predictable equipments. Transformer bushings account for the majority of transformer faults. Hence, to uphold the integrity of the power transmission and dis- tribution system, a tool to detect and identify faults in their developing stage is necessary in transformer bushings. Among the numerous tools for bushings monitoring, dissolved gas analysis (DGA) is the most commonly used. The advances in DGA and data storage capabilities have resulted in large amount of data and ultimate
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Kulkarni, Ruturaj Jayant. "AI Based Modelling and Optimization of Turning Process." 2012. http://hdl.handle.net/1805/3418.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>In this thesis, Artificial Neural Network (ANN) technique is used to model and simulate the Turning Process. Significant machining parameters (i.e. spindle speed, feed rate, and, depths of cut) and process parameters (surface roughness and cutting forces) are considered. It is shown that Multi-Layer Back Propagation Neural Network is capable to perform this particular task. Design of Experiments approach is used for efficient selection of values of parameters used during experiments to reduce cost and time for experiments. The Partic
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Leitão, Bruno Miguel Direito Pereira. "Development of classification methods for real-time seizure prediction." Doctoral thesis, 2013. http://hdl.handle.net/10316/23583.

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Tese de doutoramento do Programa de Doutoramento em Ciências e Tecnologias da Informação, apresentada à Faculdade de Ciências e Tecnologia da Universidade de Coimbra.<br>In the last decades, the scientific community has made enormous efforts to understand the basic mechanisms underlying the generation of epileptic seizures. The analysis of the pre-ictal dynamics among different brain regions has been shown as an important source of information towards the understanding of the spatio-temporal mechanisms. This study, partially a contribution to the EPILEPSIAE project, aims the prediction of
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Pilarski, Patrick Michael. "Computational analysis of wide-angle light scattering from single cells." Phd thesis, 2009. http://hdl.handle.net/10048/774.

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Thesis (Ph.D.)--University of Alberta, 2009.<br>Title from PDF file main screen (viewed on Apr. 1, 2010). A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Doctor of Philosophy, Department of Electrical and Computer Engineering, University of Alberta. Includes bibliographical references.
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Kuan-ChiehHuang and 黃冠傑. "Multi-modal Emotion Recognition Method based on Computational Intelligence Techniques." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/02095424907388062413.

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博士<br>國立成功大學<br>資訊工程學系<br>102<br>Affective communication is an essential daily interaction skill, which is also desired for use in digital artifacts. To learn this skill, digital artifacts need to build a prerequisite ability of emotion recognition. However, it is still a challenging issue because people recognize emotions using a highly complex process influenced by many vague factors. The technical solutions in digital world have not yet been able to fully mimic such process. This study therefore proposes a collaborative emotion recognition method that is realized by multiple virtual expert
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Te-Wei, Kao, and 高德偉. "Applying Intelligent Computational Methods for Optimizing the Parameters of Plating Film Process." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/58388610875426169510.

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碩士<br>義守大學<br>電機工程學系碩士在職專班<br>101<br>Plating Film Process of Plasma Enhanced Chemical Vapor Deposition (CVD) is a technique which usually has the complex and nonlinear chemical and physical reactions, non-robust and variations. These conditions certainly will determine the success of the whole manufacturing process. Thus, how to precisely adjust the control parameters of the manufacturing process, improve the good rate of product, and decrease the number of parameter’s adjustment has become an essential work of an engineer. It is well known that many control parameters need to be considered an
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CHEN, YU, and 陳佑. "Apply Six Sigma to Screen Printing Quality Improvement based on Taguchi Method and Computational Intelligence Technique." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/353gce.

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碩士<br>國立臺北大學<br>企業管理學系<br>107<br>To fulfill electronic device’s fast-change and innovative fancy design requirement, transparent series color ink with LED backlit design is massively applied in the industry. Because the composition of transparent color ink is quite different from traditional ink, it is difficult to control the printing flatness, quality consistency and backlit performance. The manufacture process is lack of systematic control. According to the high inspection standard of electronic device, the manufacture showed low yield and high quality cost. This study followed the fram
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Akova, Ferit. "A nonparametric Bayesian perspective for machine learning in partially-observed settings." Thesis, 2014. http://hdl.handle.net/1805/4825.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>Robustness and generalizability of supervised learning algorithms depend on the quality of the labeled data set in representing the real-life problem. In many real-world domains, however, we may not have full knowledge of the underlying data-generating mechanism, which may even have an evolving nature introducing new classes continually. This constitutes a partially-observed setting, where it would be impractical to obtain a labeled data set exhaustively defined by a fixed set of classes. Traditional supervised learning algorithms, a
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Wu, Shang-Lin, and 吳尚林. "Brain Computer-Interface System: from Signal Measurement Circuit System Design to Computational Intelligence Method and its Application." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/4bp2se.

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博士<br>國立交通大學<br>電控工程研究所<br>105<br>Significant advances in neuroscience, sensor technologies, and efficient signal processing algorithms have greatly facilitated the transition from laboratory-oriented neuroscience research to practical applications. Brain-computer interfaces (BCIs) represent major strides in translating brain signals into actionable decisions and primarily consist of front-end signal processing and back-end signal analyzing that guide the communications between users and systems. This dissertation presents several current neuro network technologies and computational intelligen
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Zeghbib, Abdelhafid [Verfasser]. "Forearm surface EMG signals recognition and muscoloskeletal system dynamics identification using intelligent computational methods / von Abdelhafid Zeghbib." 2008. http://d-nb.info/987495402/34.

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Patzwahl, Steffen Wernstedt Jürgen. "Einsatz von Methoden der Computational Intelligence auf Mikrocontrollersystemen zur Realisierung von Prozessführungssystemen am Beispiel der anaeroben Biogasfermentation /." 2004. http://www.gbv.de/dms/ilmenau/toc/480248737.PDF.

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Nagelberg, Alan. "MICA: A Hybrid Method for Corpus-Based Algorithmic Composition of Music Based on Genetic Algorithms, Zipf's Law, and Markov Models." 2014. http://hdl.handle.net/1993/23263.

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An algorithm known as the Musical Imitation and Creativity Algorithm (MICA) that composes stylistic music based on a corpus of works in a given style is presented. The corpus works are digital music scores created from the widely available MIDI format. The algorithm restricts the note placement in compositions using a Markov chain model built from discrete-time representations of the corpus pieces. New compositions are evolved using a genetic algorithm with a fitness function based on Zipf's Law properties of various musical metrics in the corpus pieces. The resulting compositions are evaluate
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Zhou, Li, University of Western Sydney, College of Health and Science, and School of Computing and Mathematics. "Development and applications of moving least square Ritz method in science and engineering computation." 2007. http://handle.uws.edu.au:8081/1959.7/13521.

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A detailed literature review on the development and applications of several numerical methods in solid mechanics and electromagnetic field analysis is presented in the thesis. Despite the great achievements in this research area, there are always the needs to develop new numerical methods or to explore alternative techniques for the purpose of solving the complicate problems and improve the efficiency and accuracy of the existing or new numerical methods. This thesis presents the development of a novel numerical method, the moving least square Ritz (MLS-Ritz) method, and its applications for s
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Zhou, Li. "Development and applications of moving least square Ritz method in science and engineering computation." Thesis, 2007. http://handle.uws.edu.au:8081/1959.7/13521.

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A detailed literature review on the development and applications of several numerical methods in solid mechanics and electromagnetic field analysis is presented in the thesis. Despite the great achievements in this research area, there are always the needs to develop new numerical methods or to explore alternative techniques for the purpose of solving the complicate problems and improve the efficiency and accuracy of the existing or new numerical methods. This thesis presents the development of a novel numerical method, the moving least square Ritz (MLS-Ritz) method, and its applications for s
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Saborío, Morales Juan Carlos. "Relevance-based Online Planning in Complex POMDPs." Doctoral thesis, 2020. https://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-202007173302.

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Planning under uncertainty is a central topic at the intersection of disciplines such as artificial intelligence, cognitive science and robotics, and its aim is to enable artificial agents to solve challenging problems through a systematic approach to decision-making. Some of these challenges include generating expectations about different outcomes governed by a probability distribution and estimating the utility of actions based only on partial information. In addition, an agent must incorporate observations or information from the environment into its deliberation process and produce the n
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Cioboiu, Emilia Alina. "L’analyse de composants émotionnels dans des stratégies d’apprentissage." Thèse, 2009. http://hdl.handle.net/1866/3744.

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Un certain nombre de théories pédagogiques ont été établies depuis plus de 20 ans. Elles font appel aux réactions de l’apprenant en situation d’apprentissage, mais aucune théorie pédagogique n’a pu décrire complètement un processus d’enseignement en tenant compte de toutes les réactions émotionnelles de l’apprenant. Nous souhaitons intégrer les émotions de l’apprenant dans ces processus d’apprentissage, car elles sont importantes dans les mécanismes d’acquisition de connaissances et dans la mémorisation. Récemment on a vu que le facteur émotionnel est considéré jouer un rôle très important d
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(9805406), Md Rahat Hossain. "A novel hybrid method for solar power prediction." Thesis, 2013. https://figshare.com/articles/thesis/A_novel_hybrid_method_for_solar_power_prediction/13432601.

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Renewable energy sources, particularly solar energy, play a vital role for generating environment-friendly electricity. Foremost advantages of solar energy sources are: nonpolluting, free in terms of availability and renewable. The renewable green-energy sources are becoming more cost-effective and sustainable substitutes to conventional fossil fuels. Nonetheless, power generation from Photovoltaic (PV) systems is unpredictable due to its reliance on meteorological conditions. The effective use of this fluctuating solar energy source obliges reliable and robust forecast information for managem
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(8771429), Ashley S. Dale. "3D OBJECT DETECTION USING VIRTUAL ENVIRONMENT ASSISTED DEEP NETWORK TRAINING." Thesis, 2021.

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<div> <div> <div> <p>An RGBZ synthetic dataset consisting of five object classes in a variety of virtual environments and orientations was combined with a small sample of real-world image data and used to train the Mask R-CNN (MR-CNN) architecture in a variety of configurations. When the MR-CNN architecture was initialized with MS COCO weights and the heads were trained with a mix of synthetic data and real world data, F1 scores improved in four of the five classes: The average maximum F1-score of all classes and all epochs for the networks trained with synthetic data is F1∗ = 0.91, compared t
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