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Rozprawy doktorskie na temat „Fuzzy K-means”

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Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Hong, Sui. "Experiments with K-Means, Fuzzy c-Means and Approaches to Choose K and C." Honors in the Major Thesis, University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/1224.

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This item is only available in print in the UCF Libraries. If this is your Honors Thesis, you can help us make it available online for use by researchers around the world by following the instructions on the distribution consent form at http://library.ucf<br>Bachelors<br>Engineering and Computer Science<br>Computer Engineering

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Camara, Assa. "Využití fuzzy množin ve shlukové analýze se zaměřením na metodu Fuzzy C-means Clustering." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-417051.

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This master thesis deals with cluster analysis, more specifically with clustering methods that use fuzzy sets. Basic clustering algorithms and necessary multivariate transformations are described in the first chapter. In the practical part, which is in the third chapter we apply fuzzy c-means clustering and k-means clustering on real data. Data used for clustering are the inputs of chemical transport model CMAQ. Model CMAQ is used to approximate concentration of air pollutants in the atmosphere. To the data we will apply two different clustering methods. We have used two different methods to s

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Schenatto, Kelyn. "Utilização de métodos de interpolação e agrupamento para definição de unidades de manejo em agricultura de precisão." Universidade Estadual do Oeste do Parana, 2014. http://tede.unioeste.br:8080/tede/handle/tede/178.

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Made available in DSpace on 2017-05-12T14:46:57Z (GMT). No. of bitstreams: 1 Kelyn Schenatto.pdf: 4212903 bytes, checksum: 0ba04350cc25aff5e6acb249938e5375 (MD5) Previous issue date: 2014-02-04<br>Despite the benefits offered by the technology of precision agriculture (PA), the necessity of dense sampling grids and use of sophisticated equipment for the soil and plant handling make it financially unfeasible in many cases, especially for small producers. With the aimof making viable the PA, the definition of management zones (MZ) consists in dividing the plotin subregions that have similar ph

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Quinteiro, José António Teixeira. "Segmentação de individuos no Facebook que gostam de música: abordagem exploratória, recorrendo à comparação entre dois algoritmos, k-means e fuzzy c-means." Master's thesis, Instituto Superior de Economia e Gestão, 2011. http://hdl.handle.net/10400.5/4338.

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Mestrado em Gestão/MBA<br>Para se poder definir os melhores planos estratégicos, as decisões de marketing que se têm que tomar, com o intuito de abordar o mercado, escolher a melhor campanha publicitária, seleccionar o segmento e o tipo de produto ou serviço a oferecer, têm que ter por base o resultado de uma boa análise técnica da informação ou dos dados disponíveis. A escolha do método de segmentação, é de primordial importância, pois os dados que se obtêm podem alterar a estratégia de selecção do mercado alvo e a estratégia de posicionamento dos produtos ou serviços, para além dos custos in

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Klen, André Monteiro. "Algoritmo para agrupamento de descontinuidades em famílias baseado no Método Fuzzy K-Means." reponame:Repositório Institucional da UFOP, 2015. http://www.repositorio.ufop.br/handle/123456789/5705.

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Programa de Pós-Graduação em Geotecnia. Núcleo de Geotecnia, Escola de Minas, Universidade Federal de Ouro Preto.<br>Submitted by Oliveira Flávia (flavia@sisbin.ufop.br) on 2015-10-16T16:50:52Z No. of bitstreams: 2 license_rdf: 19418 bytes, checksum: 6dde0d96f18aca4c252a500311f54121 (MD5) TESE_AlgoritmoAgrupamentoDescontinuidades.pdf: 4101321 bytes, checksum: 68c6eec732bdc99941712e49b4cf8c3e (MD5)<br>Approved for entry into archive by Gracilene Carvalho (gracilene@sisbin.ufop.br) on 2015-10-29T18:48:25Z (GMT) No. of bitstreams: 2 license_rdf: 19418 bytes, checksum: 6dde0d96f18aca4c252a500311f

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Chahine, Firas Safwan. "A Genetic Algorithm that Exchanges Neighboring Centers for Fuzzy c-Means Clustering." NSUWorks, 2012. http://nsuworks.nova.edu/gscis_etd/116.

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Clustering algorithms are widely used in pattern recognition and data mining applications. Due to their computational efficiency, partitional clustering algorithms are better suited for applications with large datasets than hierarchical clustering algorithms. K-means is among the most popular partitional clustering algorithm, but has a major shortcoming: it is extremely sensitive to the choice of initial centers used to seed the algorithm. Unless k-means is carefully initialized, it converges to an inferior local optimum and results in poor quality partitions. Developing improved method for se

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Drach, Tetjana Oleksandrivna, and Oleksandr Evgenovich Goloskokov. "Research and development of mathematical and software solutions of the information system of situational enterprise management." Thesis, NTU "KhPI", 2018. http://repository.kpi.kharkov.ua/handle/KhPI-Press/38079.

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Zubková, Kateřina. "Text mining se zaměřením na shlukovací a fuzzy shlukovací metody." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2018. http://www.nusl.cz/ntk/nusl-382412.

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This thesis is focused on cluster analysis in the field of text mining and its application to real data. The aim of the thesis is to find suitable categories (clusters) in the transcribed calls recorded in the contact center of Česká pojišťovna a.s. by transferring these textual documents into the vector space using basic text mining methods and the implemented clustering algorithms. From the formal point of view, the thesis contains a description of preprocessing and representation of textual data, a description of several common clustering methods, cluster validation, and the application its

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LIMA, Flávia Ayana Nascimento de. "Agrupamento de fornos de redução de alumínio utilizando os algoritmos Affinity Propagation, Mapa auto–organizável de Kohonen (som), Fuzzy C–Means e K–Means." Universidade Federal do Pará, 2017. http://repositorio.ufpa.br/jspui/handle/2011/9470.

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Submitted by Marina Farias (mgmf@ufpa.br) on 2018-02-21T13:19:33Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_AgrupamentoFornosReducao.pdf: 6297988 bytes, checksum: 9e3c95180dbdfbdbc60f142c239aeb87 (MD5)<br>Approved for entry into archive by Marina Farias (mgmf@ufpa.br) on 2018-02-21T13:23:06Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_AgrupamentoFornosReducao.pdf: 6297988 bytes, checksum: 9e3c95180dbdfbdbc60f142c239aeb87 (MD5)<br>Made available in DSpace on 2018-

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Nguiffo, Podie Yves. "Segmentation d'images de transmission pour la correction de l'atténué en tomographie d'émission par positrons." Mémoire, Université de Sherbrooke, 2009. http://savoirs.usherbrooke.ca/handle/11143/3993.

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L'atténuation des photons est un phénomène qui affecte directement et de façon profonde la qualité et l'information quantitative obtenue d'une image en Tomographie d'Emission par Positrons (TEP). De sévères artefacts compliquant l'interprétation visuelle ainsi que de profondes erreurs d'exactitudes sont présents lors de l'évaluation quantitative des images TEP, biaisant la vérification de la corrélation entre les concentrations réelles et mesurées.L' atténuation est due aux effets photoélectrique et Compton pour l'image de transmission (30 keV - 140 keV), et majoritairement à l'effet Compton p

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Hespanhol, Patrícia Freitas Pelozo. "Análise de padrões na produção de cana de açúcar utilizando aprendizado de máquina /." Tupã, 2019. http://hdl.handle.net/11449/183121.

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Orientador: Luís Roberto Almeida Gabriel Filho<br>Coorientador: Luiz Fernando Sommaggio Coletta<br>Coorientador: Camila Pires Cremasco Gabriel<br>Resumo: O presente trabalho buscou identificar padrões na produção de cana de por meio da utilização de Inteligência Artificial. Para tanto, foi realizada coleta de informações de fontes secundárias, com dados estatísticos fornecidos por órgãos públicos sobre a área cultivada e a produção de cana de açúcar, índices como pluviométricos e de temperatura e o tipo de solo dos municípios do estado de São Paulo, no ano de 2017, por meio de pesquisa documen

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Hughes, M. Joseph. "Determining biogeochemical assemblages on the Stony River, Grant County, WV, using fuzzy c-means and k-nearest neighbors clustering." Huntington, WV : [Marshall University Libraries], 2006. http://www.marshall.edu/etd/descript.asp?ref=723.

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Kerwin, Matthew. "Comparison of Traditional Image Segmentation Techniques and Geostatistical Threshold." Thesis, James Cook University, 2006. https://eprints.qut.edu.au/99764/1/kerwin-honours-thesis.pdf.

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A general introduction to image segmentation is provided, including a detailed description of common classic techniques: Otsu’s threshold, <i>k</i>-means and fuzzy <i>c</i>-means clustering; and suggestions of ways in which these techniques have been subsequently modified for special situations. Additionally, a relatively new approach is described, which attempts to address certain exposed failings of the classic techniques listed by incorporating a spatial statistical analysis technique commonly used in geological studies. Results of different segmentation techniques are calculated for

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Hudson, Cody Landon. "Protein structure analysis and prediction utilizing the Fuzzy Greedy K-means Decision Forest model and Hierarchically-Clustered Hidden Markov Models method." Thesis, University of Central Arkansas, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1549796.

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<p>Structural genomics is a field of study that strives to derive and analyze the structural characteristics of proteins through means of experimentation and prediction using software and other automatic processes. Alongside implications for more effective drug design, the main motivation for structural genomics concerns the elucidation of each protein’s function, given that the structure of a protein almost completely governs its function. Historically, the approach to derive the structure of a protein has been through exceedingly expensive, complex, and time consuming methods such as x

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Souza, Jackson Gomes de. "T?cnicas de computa??o natural para segmenta??o de imagens m?dicas." Universidade Federal do Rio Grande do Norte, 2009. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15282.

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Made available in DSpace on 2014-12-17T14:55:35Z (GMT). No. of bitstreams: 1 JacksonGS.pdf: 1963039 bytes, checksum: ed3464892d7bb73b5dcab563e42f0e01 (MD5) Previous issue date: 2009-09-28<br>Image segmentation is one of the image processing problems that deserves special attention from the scientific community. This work studies unsupervised methods to clustering and pattern recognition applicable to medical image segmentation. Natural Computing based methods have shown very attractive in such tasks and are studied here as a way to verify it's ap

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Guder, Mennan. "Data Mining Methods For Clustering Power Quality Data Collected Via Monitoring Systems Installed On The Electricity Network." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12611120/index.pdf.

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Increasing power demand and wide use of high technology power electronic devices result in need for power quality monitoring. The quality of electric power in both transmission and distribution systems should be analyzed in order to sustain power system reliability and continuity. This analysis is possible by examination of data collected by power quality monitoring systems. In order to define the characteristics of the power system and reveal the relations between the power quality events, huge amount of data should be processed. In this thesis, clustering methods for power quality events are

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Bacak, Hikmet Ozge. "Decision Making System Algorithm On Menopause Data Set." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12612471/index.pdf.

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Multiple-centered clustering method and decision making system algorithm on menopause data set depending on multiple-centered clustering are described in this study. This method consists of two stages. At the first stage, fuzzy C-means (FCM) clustering algorithm is applied on the data set under consideration with a high number of cluster centers. As the output of FCM, cluster centers and membership function values for each data member is calculated. At the second stage, original cluster centers obtained in the first stage are merged till the new numbers of clusters are reached. Merging process

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Trinh, Viet. "CONTEXTUALIZING OBSERVATIONAL DATA FOR MODELING HUMAN PERFORMANCE." Doctoral diss., University of Central Florida, 2009. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2747.

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This research focuses on the ability to contextualize observed human behaviors in efforts to automate the process of tactical human performance modeling through learning from observations. This effort to contextualize human behavior is aimed at minimizing the role and involvement of the knowledge engineers required in building intelligent Context-based Reasoning (CxBR) agents. More specifically, the goal is to automatically discover the context in which a human actor is situated when performing a mission to facilitate the learning of such CxBR models. This research is derived from the contextu

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Hunter, Brandon. "Channel Probing for an Indoor Wireless Communications Channel." BYU ScholarsArchive, 2003. https://scholarsarchive.byu.edu/etd/64.

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The statistics of the amplitude, time and angle of arrival of multipaths in an indoor environment are all necessary components of multipath models used to simulate the performance of spatial diversity in receive antenna configurations. The model presented by Saleh and Valenzuela, was added to by Spencer et. al., and included all three of these parameters for a 7 GHz channel. A system was built to measure these multipath parameters at 2.4 GHz for multiple locations in an indoor environment. Another system was built to measure the angle of transmission for a 6 GHz channel. The addition of th

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Chang, Tsun-Chuan, and 張宗荃. "Speeding up Fuzzy k-Means Clustering Algorithm on GPU." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/70355858766705138770.

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碩士<br>國立臺灣海洋大學<br>資訊工程學系<br>103<br>Recently the hardware aspect of the computer has gradually become more developed and advanced in order to keep up with the rise in data and computational efficiency. The graphics processing unit (GPU) is one of the hardware that has followed that trait. The ability of the GPU to do ﬂoating point operations has exceeded that of the CPU due to the massive parallel architecture within the GPU, which has also become a powerful technology for programming purposes. Data clustering is also an important issue in data mining, but the applications of data clustering ar

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賴仁傑. "Generalized Fuzzy k-Means Clustering Using m Nearest Cluster Centers." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/19302324043911615857.

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Urbanová, Zuzana. "Optimalizace rozvržení provozu ve firmě Vodárenská akciová společnost a.s." Master's thesis, 2014. http://www.nusl.cz/ntk/nusl-177137.

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Dimploma thesis deals with the optimization of operation distribution in company Vodárenská akciová společnost, a.s. Aim of the thesis is to determine achievement standards of companies branches and to state the capacity reserves for every one of them. Next, using methods of cluster analysis and graph theory, proposing recommendation leading to effective utilization of operation capacity. This is done by optimizing total number of business branches and subsequent creation of new regions. Thesis consists of theoretical and practical part. In this papers theoretical part, hierarchical and nonhie

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KUMAR, ARVIND. "FUZZY CLUSTERING FOR COLOR IMAGE SEGMENTATION USING GRAVITATIONAL SEARCH ALGORITHM." Thesis, 2016. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15400.

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Clustering is a key activity in numerous data mining applications such as information retrieval, text mining, image segmentation, etc. This research work proposes a clustering approach, Fuzzy-GSA, based on gravitational search algorithm (GSA). In the proposed Fuzzy-GSA approach, a fuzzy inference system is developed to effectively control the parameters of GSA. The performance of the Fuzzy-GSA algorithm is evaluated against four benchmark datasets from the UC Irvine repository. The results illustrate that the Fuzzy-GSA approach attains the highest quality clustering over the selected dat

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Lin, Zhuo-Yi, and 林卓毅. "The Development of an Expert Landslide System through Fuzzy C-means and K-means+ Particle Swarm Optimization." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/32722307926814177974.

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碩士<br>國立中興大學<br>土木工程學系所<br>99<br>Spatial information of landslide interpretation is usually analyzed statistically based on topography, vegetation conditions and landforms. However, the uncertainty and the massive volume of data, the determination of landslide occurrence will result in many misjudgments. Hence, this study is decided to develop the clustering techniques to extract out some knowledge from landslide occurrence. More specifically, this study used spatial information technology (RS and DEM) to attain the vegetation cover and the landforms. Ancillary information is also adopted to

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Wu, Meng-Chian, and 吳孟謙. "Exploring the Effectiveness of Combining ICA with K-means and Fuzzy C-means in Brain Tissue Classification." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/67497985313602266520.

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碩士<br>國立中興大學<br>電機工程學系所<br>98<br>This paper presents an application of using a widely used clustering algorithm, called k-means and fuzzy c-means to get several types of binary images for MR brain image classification. First, we use independent component analysis (ICA) to enhance the components of our original images to reduce the influence of noise. Then we use k-means or fuzzy c-means to get the first classified images. But if the original images have noise, k-means and fuzzy c-means can’t deal with it very well. Fisher’s linear discriminate analysis (FLDA) which performs classification iter

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Chieh-Ming, Lin, and 林杰民. "A study of K-Means algorithm for clustering problems with fuzzy linguistic attributes." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/09624139013587320676.

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碩士<br>國立勤益技術學院<br>工業工程與管理系<br>93<br>The generalized k-means method is based on the measurements through a predetermined penalty function that measures the discrepancy of assigning data of a dataset to k clusters with k points as their centres. The k central points and the assignment are modified based on the intention of minimizing the measurements. This method has been applied to data analysis and the decision-making problems. Since some decision-making problems have to deal with the data that collected with imprecision attributes, we extend its application capability in this study. The lingu

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Hsiu, Min, and 何旻修. "The Research of Using Agglomerative Fuzzy K-Means Clustering in Latent Semantic Indexing." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/35507679547671787463.

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碩士<br>國立中央大學<br>資訊管理研究所<br>98<br>Due to high cost of computing latent semantic indexing has not been popular, and full computing of large datasets is still too expensive is concerned by some scholars recently, and some strategies is improved based on clustering, that allow users to query keywords with little effort on comparing with similar clusters and reduce computational cost. However, those studies using the strategies based on clustering can only be compared with a fixed number of comparisons, and the query results are limited. The Agglomerative Fuzzy K-Means Clustering algorithm is p

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Jian, Wen-Shan, and 簡文珊. "Fuzzy Forecasting Based on Fuzzy Logical Relationships, Fuzzy-Trend Logical Relationship Groups, K-Means Clustering Algorithm, Similarity Measures and Particle Swarm Optimization Techniques." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/54195019537890008557.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>103<br>In this thesis, we propose two new fuzzy forecasting methods to deal with forecasting problems based on fuzzy logical relationships, fuzzy-trend logical relationship groups, K-means clustering algorithm, similarity measures and particle swarm optimization (PSO) techniques. In the first method of this thesis, we propose a new method for forecasting the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy time series, fuzzy logical relationships, particle swarm optimization (PSO) techniques, the K-means clustering algorithm, and simil

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Jakubík, Miroslav. "RBF-sítě s dynamickou architekturou." Master's thesis, 2011. http://www.nusl.cz/ntk/nusl-297903.

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In this master thesis I recapitulated several methods for clustering input data. Two well known clustering algorithms, concretely K-means algorithm and Fuzzy C-means (FCM) algorithm, were described in the submitted work. I presented several methods, which could help estimate the optimal number of clusters. Further, I described Kohonen maps and two models of Kohonen's maps with dynamically changing structure, namely Kohonen map with growing grid and the model of growing neural gas. At last I described quite new model of radial basis function neural networks. I presented several learning algorit

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Jakubík, Miroslav. "RBF-sítě s dynamickou architekturou." Master's thesis, 2012. http://www.nusl.cz/ntk/nusl-304160.

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In this master thesis I recapitulated several methods for data clustering. Two well known clustering algorithms, concretely K-means algorithm and Fuzzy C-means (FCM) algorithm, were described in the submitted work. I presented several methods, which could help estimate the optimal number of clusters. Further, I described Kohonen maps and two models of Kohonen's maps with dynamically changing structure, namely Kohonen map with growing grid and the model of growing neural gas. At last I described quite new model of radial basis function neural networks. I presented several learning algorithms fo

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Vu, Dinh-Trung, and 武亭忠. "Speeding up Generalized Fuzzy k-Means Clustering Using m Nearest Cluster Centers Algorithm on GPU." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/57171878116760062942.

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碩士<br>國立臺灣海洋大學<br>資訊工程學系<br>103<br>The graphics hardware is becoming increasingly more powerful and programmable with the introduction of Graphics Processing Units (GPU) like the NVidia GeForce series. The GPU’s exceed the ordinary general purpose CPU’s ability to do ﬂoating point operations due to the massively parallel architecture in the GPU’s. With the newest GPU’s one actually have enough programmable freedom to do other computations than computer graphics processing. This project will take advantage of this in order to get high performance implementations of data clustering algorithms. I

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Chuang, Yi-Tang, and 莊易蒼. "Self-Splitting K-Means Generated Neural Fuzzy System with Support Vector Regression for Illumination Estimation." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/09058589041746215818.

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碩士<br>修平科技大學<br>電機工程研究所<br>100<br>This paper proposes a Self-Splitting K-Means generated Neural Fuzzy System with Support Vector Regression (SSKNFS-SVR). The consequent layer in SSKNFS-SVR is a Takagi-Sugeno-Kang (TSK)-type or singleton consequent. For structure learning, a Self-Splitting K-Means algorithm clusters the input training data and determines the rule number. For parameter learning, a linear support vector regression (SVR) algorithm is proposed to tune free parameters in the consequent part. The motivation for using SVR for parameter learning is to improve the SSKNFS-SVR generalizat

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Chen, Yi-Huan, and 陳禕寰. "Integration of ART2 Neural Network Based K-means and PrefixSpan Algorithm For Fuzzy Sequential Patterns Mining." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/8wvf88.

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碩士<br>國立臺北科技大學<br>工業工程與管理研究所<br>99<br>The development of information technology has improved the data storage and retrieval problems, such as science data, medical data, population data, financial data, market data, etc. How to find useful information from those data has become the most important issue. Thus, this study intends to propose an integrated method for mining important sequential patterns. First, apply the k-means clustering to find the clustering boundaries from results of ART2. Second, find the appropriate fuzzy set for fuzzy sequential patterns. Finally, apply the PrefixSpan algo

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Luna, Laura Isabel. "Análisis de componenetes principales con datos georeferenciados. Una aplicación en la industria turística." Master's thesis, 2017. http://hdl.handle.net/11086/13306.

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Tesis (Maestría en Estadística Aplicada) -- Universidad Nacional de Córdoba. Facultad de Ciencias Económicas. Escuela de Graduados ; Argentina, 2017.<br>El análisis espacial de las actividades características del turismo permite generar información relativa a la estructura de la industria turística, información necesaria para la toma de decisiones. En este trabajo se propuso realizar un mapeo de las actividades características del turismo en departamentos de Córdoba, Argentina. La innovación metodológica consiste en la generación de estadísticas para datos espaciales multidimensionales. Se es

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Wojtusik, Jacek. "Wielomodele diagnostyczne maszyn wirnikowych." Rozprawa doktorska, 2005. https://repolis.bg.polsl.pl/dlibra/docmetadata?showContent=true&id=5197.

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Wojtusik, Jacek. "Wielomodele diagnostyczne maszyn wirnikowych." Rozprawa doktorska, 2005. https://delibra.bg.polsl.pl/dlibra/docmetadata?showContent=true&id=5197.

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