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Dissertations / Theses on the topic 'Fuzzyc- means clustering'

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Published: 3 June 2025

Last updated: 31 July 2025

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1

Parker, Jonathon Karl. "Accelerated Fuzzy Clustering." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4929.

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Clustering algorithms are a primary tool in data analysis, facilitating the discovery of groups and structure in unlabeled data. They are used in a wide variety of industries and applications. Despite their ubiquity, clustering algorithms have a flaw: they take an unacceptable amount of time to run as the number of data objects increases. The need to compensate for this flaw has led to the development of a large number of techniques intended to accelerate their performance. This need grows greater every day, as collections of unlabeled data grow larger and larger. How does one increase the spe

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2

Kanade, Parag M. "Fuzzy ants as a clustering concept." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000397.

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3

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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4

Naik, Vaibhav C. "Fuzzy C-means clustering approach to design a warehouse layout." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000437.

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5

FURUHASHI, Takeshi, and Makoto YASUDA. "Fuzzy Entropy Based Fuzzy c-Means Clustering with Deterministic and Simulated Annealing Methods." Institute of Electronics, Information and Communication Engineers, 2009. http://hdl.handle.net/2237/15060.

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6

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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7

Beca, Cofre Sebastián. "Clustering Difuso con Selección de Atributos." Tesis, Universidad de Chile, 2007. http://www.repositorio.uchile.cl/handle/2250/104686.

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8

Stetco, Adrian. "An investigation into fuzzy clustering quality and speed : fuzzy C-means with effective seeding." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/an-investigation-into-fuzzy-clustering-quality-and-speed-fuzzy-cmeans-with-effective-seeding(fac3eab2-919a-436c-ae9b-1109b11c1cc2).html.

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Cluster analysis, the automatic procedure by which large data sets can be split into similar groups of objects (clusters), has innumerable applications in a wide range of problem domains. Improvements in clustering quality (as captured by internal validation indexes) and speed (number of iterations until cost function convergence), the main focus of this work, have many desirable consequences. They can result, for example, in faster and more precise detection of illness onset based on symptoms or it could provide investors with a rapid detection and visualization of patterns in financial time

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9

Altinel, Fatih. "An Empirical Study On Fuzzy C-means Clustering For Turkish Banking System." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12615027/index.pdf.

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Banking sector is very sensitive to macroeconomic and political instabilities and they are prone to crises. Since banks are integrated with almost all of the economic agents and with other banks, these crises affect entire societies. Therefore, classification or rating of banks with respect to their credibility becomes important. In this study we examine different models for classification of banks. Choosing one of those models, fuzzy c-means clustering, banks are grouped into clusters using 48 different ratios which can be classified under capital, assets quality, liquidity, profitability, in

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10

Chakeri, Alireza. "Scalable Clustering Using the Dempster-Shafer Theory of Evidence." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6478.

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Clustering large data sets has become very important as the amount of available unlabeled data increases. Single Pass Fuzzy C-Means (SPFCM) is useful when memory is too limited to load the whole data set. The main idea is to divide dataset into several chunks and to apply fuzzy c-means (FCM) to each chunk. SPFCM uses the weighted cluster centers of the previous chunk in the next data chunks. However, when the number of chunks is increased, the algorithm shows sensitivity to the order in which the data is processed. Hence, we improved SPFCM by recognizing boundary and noisy data in each chunk a

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11

Hore, Prodip. "Scalable frameworks and algorithms for cluster ensembles and clustering data streams." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002135.

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12

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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13

Gu, Yuhua. "Ant clustering with consensus." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0002959.

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14

Turner, Kevin Michael. "Estimation of Ocean Water Chlorophyll-A Concentration Using Fuzzy C-Means Clustering and Artificial Neural Networks." Fogler Library, University of Maine, 2007. http://www.library.umaine.edu/theses/pdf/TurnerKM2007.pdf.

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15

FANEGAN, JULIUS BOLUDE. "A FUZZY MODEL FOR ESTIMATING REMAINING LIFETIME OF A DIESEL ENGINE." University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1188951646.

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16

Rodgers, Sarah. "Application of the fuzzy c-means clustering algorithm to the analysis of chemical structures." Thesis, University of Sheffield, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.412772.

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17

Rapstine, Thomas D. "Gravity gradiometry and seismic interpretation integration using spatially guided fuzzy c-means clustering inversion." Thesis, Colorado School of Mines, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1602383.

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<p> Gravity gradiometry has been used as a geophysical tool to image salt structure in hydrocarbon exploration. The knowledge of the location, orientation, and spatial extent of salt bodies helps characterize possible petroleum prospects. Imaging around and underneath salt bodies can be challenging given the petrophysical properties and complicated geometry of salt. Methods for imaging beneath salt using seismic data exist but are often iterative and expensive, requiring a refinement of a velocity model at each iteration. Fortunately, the relatively strong density contrast between salt and bac

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18

Milagre, Selma Terezinha. "Análise do número de grupos em bases de dados incompletas utilizando agrupamentos nebulosos e reamostragem Bootstrap." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/18/18153/tde-04032009-150315/.

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A técnica de agrupamento de dados é amplamente utilizada em análise exploratória, a qual é frequentemente necessária em diversas áreas de pesquisa tais como medicina, biologia e estatística, para avaliar potenciais hipóteses a serem utilizadas em estudos subseqüentes. Em bases de dados reais, a ocorrência de dados incompletos, nos quais os valores de um ou mais atributos do dado são desconhecidos, é bastante comum. Este trabalho apresenta um método capaz de identificar o número de grupos presentes em bases de dados incompletas, utilizando a combinação das técnicas de agrupamentos nebulosos e r

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19

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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20

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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21

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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22

Anzano, Eugeno S. "Fuzzy Clustering Means algorithm for track fusion in U.S. Coast Guard Vessel Traffic Service systems /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1999. http://handle.dtic.mil/100.2/ADA368496.

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23

Anzano, Eugenio S. "Fuzzy Clustering Means algorithm for track fusion in U.S. Coast Guard Vessel Traffic Service systems." Thesis, Monterey, California: Naval Postgraduate School, 1999. http://hdl.handle.net/10945/13489.

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This thesis presents a fuzzy association based data fusion algorithm for U.S. Coast Guard Vessel Traffic Service (VTS) systems to reduce the number of redundant target tracks displayed to vessel traffic operators. The proposed algorithm uses the Fuzzy Clustering Means (FCM) algorithm to reduce the number of target tracks and associate duplicate tracks by determining the degree of membership for each target track. The algorithm uses current sensor data and the known sensor resolutions for measurement-to-measurement association and the selection of the most accurate sensor for tracking fused tar

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Lai, Daphne Teck Ching. "An exploration of improvements to semi-supervised fuzzy c-means clustering for real-world biomedical data." Thesis, University of Nottingham, 2014. http://eprints.nottingham.ac.uk/14232/.

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This thesis explores various detailed improvements to semi-supervised learning (using labelled data to guide clustering or classification of unlabelled data) with fuzzy c-means clustering (a ‘soft’ clustering technique which allows data patterns to be assigned to multiple clusters using membership values), with the primary aim of creating a semi-supervised fuzzy clustering algorithm that shows good performance on real-world data. Hence, there are two main objectives in this work. The first objective is to explore novel technical improvements to semi-supervised Fuzzy c-means (ssFCM) that can ad

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25

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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26

Ulucan, Serkan. "A Recommendation System Combining Context-awarenes And User Profiling In Mobile Environment." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606845/index.pdf.

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Up to now various recommendation systems have been proposed for web based applications such as e-commerce and information retrieval where a large amount of product or information is available. Basically, the task of the recommendation systems in those applications, for example the e-commerce, is to find and recommend the most relevant items to users/customers. In this domain, the most prominent approaches are collaborative filtering and content-based filtering. Sometimes these approaches are called as user profiling as well. In this work, a context-aware recommendation system is proposed for

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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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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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29

Liu, Xiaofeng. "Machinery fault diagnostics based on fuzzy measure and fuzzy integral data fusion techniques." Thesis, Queensland University of Technology, 2007. https://eprints.qut.edu.au/16456/1/Xiaofeng_Liu_Thesis.pdf.

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With growing demands for reliability, availability, safety and cost efficiency in modern machinery, accurate fault diagnosis is becoming of paramount importance so that potential failures can be better managed. Although various methods have been applied to machinery condition monitoring and fault diagnosis, the diagnostic accuracy that can be attained is far from satisfactory. As most machinery faults lead to increases in vibration levels, vibration monitoring has become one of the most basic and widely used methods to detect machinery faults. However, current vibration monitoring methods larg

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Liu, Xiaofeng. "Machinery fault diagnostics based on fuzzy measure and fuzzy integral data fusion techniques." Queensland University of Technology, 2007. http://eprints.qut.edu.au/16456/.

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With growing demands for reliability, availability, safety and cost efficiency in modern machinery, accurate fault diagnosis is becoming of paramount importance so that potential failures can be better managed. Although various methods have been applied to machinery condition monitoring and fault diagnosis, the diagnostic accuracy that can be attained is far from satisfactory. As most machinery faults lead to increases in vibration levels, vibration monitoring has become one of the most basic and widely used methods to detect machinery faults. However, current vibration monitoring methods larg

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Vargas, Rogerio Rodrigues de. "Uma nova forma de calcular os centros dos Clusters em algoritmos de agrupamento tipo fuzzy c-means." Universidade Federal do Rio Grande do Norte, 2012. http://repositorio.ufrn.br:8080/jspui/handle/123456789/17949.

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Made available in DSpace on 2014-12-17T15:47:00Z (GMT). No. of bitstreams: 1 RogerioRV_TESE.pdf: 769325 bytes, checksum: ddaac964e1c74fba3533b5cdd90927b2 (MD5) Previous issue date: 2012-03-30<br>Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior<br>Clustering data is a very important task in data mining, image processing and pattern recognition problems. One of the most popular clustering algorithms is the Fuzzy C-Means (FCM). This thesis proposes to implement a new way of calculating the cluster centers in the procedure of FCM algorithm which are called ckMeans, and in some variant

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Soumi, Ghosh. "A Quasi Stationary Service Architecture for Network Monitoring and Connectivity Prediction in Aeronautical Ad Hoc Network Using Fuzzy C Means Clustering." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31495.

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An Aeronautical Ad Hoc Network (AANET) of airborne elements is a high speed mobile network. The AANET has a 3D topology spread across the airspace. The high ground speed of the airborne elements changes the network topology rapidly. This makes AANET highly dynamic in nature. Upholding the connectivity in the network in such dynamic environment is a challenge. The connectivity in the network is primarily in uenced by proximity of airborne elements to each other and their relative velocities. Once an airborne element gets disconnected from the network, it becomes completely oblivious of the netw

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Pondini, Alessio. "Tenacizzazione di laminati compositi mediante l'utilizzo di nanofibre in PVDF." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8463/.

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Analisi riguardante la tenacizzazione della matrice di laminati compositi. Lo scopo è quello di aumentare la resistenza alla frattura di modo I e, a tal proposito, sono stati modificati gli interstrati di alcuni provini tramite l’introduzione di strati, di diverso spessore, di nanofibre in polivinilidenfluoruro (PVDF). La valutazione di tale metodo di rinforzo è stata eseguita servendosi di dati ottenuti tramite prove sperimentali svolte in laboratorio direttamente dal sottoscritto, che si è occupato dell’elaborazione dei dati servendosi di tecniche e algoritmi di recente ideazione. La necessi

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Fontana, Fabiane Sorbar. "Definição de zonas de manejo utilizando algoritmo de agrupamento fuzzy c-means com variadas métricas de distâncias." Universidade Estadual do Oeste do Paraná, 2017. http://tede.unioeste.br/handle/tede/3764.

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Submitted by Neusa Fagundes (neusa.fagundes@unioeste.br) on 2018-06-15T20:19:22Z No. of bitstreams: 2 Fabiane_Fontana2018.pdf: 2677532 bytes, checksum: 3036328537227cc96b8ea368e893f2fc (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Made available in DSpace on 2018-06-15T20:19:22Z (GMT). No. of bitstreams: 2 Fabiane_Fontana2018.pdf: 2677532 bytes, checksum: 3036328537227cc96b8ea368e893f2fc (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-07-19<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior -

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Shatila, Hazem Sarwat. "Adaptive Radio Resource Management in Cognitive Radio Communications using Fuzzy Reasoning." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/26618.

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As wireless technologies evolve, novel innovations and concepts are required to dynamically and automatically alter various radio parameters in accordance with the radio environment. These innovations open the door for cognitive radio (CR), a new concept in telecommunications. CR makes its decisions using an inference engine, which can learn and adapt to changes in radio conditions. Fuzzy logic (FL) is the proposed decision-making algorithm for controlling the CRâ s inference engine. Fuzzy logic is well-suited for vague environments in which incomplete and heterogeneous information is pre

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Arnaldo, Helo?na Alves. "Novos m?todos determin?sticos para gerar centros iniciais dos grupos no algoritmo fuzzy C-Means e variantes." Universidade Federal do Rio Grande do Norte, 2014. http://repositorio.ufrn.br:8080/jspui/handle/123456789/18109.

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Made available in DSpace on 2014-12-17T15:48:11Z (GMT). No. of bitstreams: 1 HeloinaAA_DISSERT.pdf: 1661373 bytes, checksum: df9fe39185a27ded472f2f72284acdf6 (MD5) Previous issue date: 2014-02-24<br>Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior<br>Data clustering is applied to various fields such as data mining, image processing and pattern recognition technique. Clustering algorithms splits a data set into clusters such that elements within the same cluster have a high degree of similarity, while elements belonging to different clusters have a high degree of dissimilarity. The

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Zettervall, Hang. "Fuzzy Set Theory Applied to Make Medical Prognoses for Cancer Patients." Doctoral thesis, Blekinge Tekniska Högskola [bth.se], Faculty of Engineering - Department of Mathematics and Natural Sciences, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00574.

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As we all know the classical set theory has a deep-rooted influence in the traditional mathematics. According to the two-valued logic, an element can belong to a set or cannot. In the former case, the element’s membership degree will be assigned to one, whereas in the latter case it takes the zero value. With other words, a feeling of imprecision or fuzziness in the two-valued logic does not exist. With the rapid development of science and technology, more and more scientists have gradually come to realize the vital importance of the multi-valued logic. Thus, in 1965, Professor Lotfi A. Zadeh

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Ataeian, Seyed Mohsen, and Mehrnaz Jaberi Darbandi. "Analysis of Quality of Experience by applying Fuzzy logic : A study on response time." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5742.

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To be successful in today's competitive market, service providers should look at user's satisfaction as a critical key. In order to gain a better understanding of customers' expectations, a proper evaluations which considers intrinsic characteristics of perceived quality of service is needed. Due to the subjective nature of quality, the vagueness of human judgment and the uncertainty about the degree of users' linguistic satisfaction, fuzziness is associated with quality of experience. Considering the capability of Fuzzy logic in dealing with imprecision and qualitative kno

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Koprnicky, Miroslav. "Towards a Versatile System for the Visual Recognition of Surface Defects." Thesis, University of Waterloo, 2005. http://hdl.handle.net/10012/888.

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Automated visual inspection is an emerging multi-disciplinary field with many challenges; it combines different aspects of computer vision, pattern recognition, automation, and control systems. There does not exist a large body of work dedicated to the design of generalized visual inspection systems; that is, those that might easily be made applicable to different product types. This is an important oversight, in that many improvements in design and implementation times, as well as costs, might be realized with a system that could easily be made to function in different production enviro

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Moura, Ronildo Pinheiro de Ara?jo. "Algoritmos de agrupamentos fuzzy intervalares e ?ndice de valida??o para agrupamento de dados simb?licos do tipo intervalo." Universidade Federal do Rio Grande do Norte, 2014. http://repositorio.ufrn.br:8080/jspui/handle/123456789/18111.

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Made available in DSpace on 2014-12-17T15:48:11Z (GMT). No. of bitstreams: 1 RonildoPAM_DISSERT.pdf: 2783175 bytes, checksum: c268ade677ca4b8c543ccc014b0aafef (MD5) Previous issue date: 2014-02-21<br>Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior<br>Symbolic Data Analysis (SDA) main aims to provide tools for reducing large databases to extract knowledge and provide techniques to describe the unit of such data in complex units, as such, interval or histogram. The objective of this work is to extend classical clustering methods for symbolic interval data based on interval-based di

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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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Wang, Yanfei. "Fuzzy methods for analysis of microarrays and networks." Thesis, Queensland University of Technology, 2011. https://eprints.qut.edu.au/48175/1/Yanfei_Wang_Thesis.pdf.

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Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) c

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Orlietti, Lorenzo. "Model Predictive Control Solutions aimed at Energy Saving and Environmental Impact Minimization." Doctoral thesis, Università Politecnica delle Marche, 2015. http://hdl.handle.net/11566/243044.

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L’esigenza di aumentare l’efficienza e la redditività degli impianti industriali e l’esigenza di rispettare rigorose norme sull’impatto ambientale, accanto alla necessità di un adeguamento a precise norme di produzione, richiedono un livello crescente di automazione. L’attività di ricerca svolta ha riguardato lo sviluppo e l’implementazione di soluzioni per l’identificazione e la modellazione di sistemi dinamici. Questi sistemi sono stati poi utilizzati al fine di progettare, implementare e testare varie politiche di controllo finalizzate al risparmio energetico. Inizialmente sono state valuta

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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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Yung-Fu, Tsai. "Multiple-pose Face Detection Using Fuzzy C-means Clustering." 2005. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0001-2607200512112000.

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Ma, Yen-Ting, and 馬嬿婷. "Sample and cluster weighted fuzzy c-means clustering algorithms." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/tpkev7.

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碩士<br>中原大學<br>應用數學研究所<br>102<br>In fuzzy cluster analysis﹐the fuzzy c-means (FCM) clustering algorithm is the most well-known and used method. Up to now﹐there are various generalizations of FCM. In order to reduce the influences of the clustering results by outliers and noisy points﹐Yu, Yang and Lee (2011) proposed sample-weighted clustering methods that apply the maximum entropy principle to automatically calculate these sample weights so as to increase the robustness of the algorithm. The purpose of this thesis is to give a cluster-weighted version of sample-weighted FCM﹐called the sample an

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Tsai, Yung-Fu, and 蔡永富. "Multiple-pose Face Detection Using Fuzzy C-means Clustering." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/27909134956224960721.

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碩士<br>國立臺灣大學<br>資訊管理學研究所<br>93<br>The challenges for face detection from images come from the variation of poses, facial expressions, occlusions, lighting conditions, and so on. We propose a method for multiple-pose face detection from still images. Our proposed method consists of three phases. First, skin pixels are extracted using a skin color model. Connected component analysis is performed to find the skin regions. Second, before extracting the feature vector of a skin region, we apply edge detection to the region. Our feature vector consists of two parts. The first part is obtained by div

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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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Liu, Shih-Hua, and 劉士華. "Sperm Whale's Voiceprint Classification via Fuzzy C-means Clustering." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/52459398101146752146.

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碩士<br>國立臺灣海洋大學<br>電機工程學系<br>104<br>Sperm whale is one species of odontoceti mammals, possesses highly developed intelligence, performs mutual communication and social activities by sending audio signals of different pulse sequence combinations. To understand the ecology of the sperm whale, we can perform voiceprint’s feature analysis and clustering from the recorded audio signals. However, background noise is corrupted into the original whale’s sound during the sound recording process, thus reducing the quality of the original whale’s sound and leading to the hardship of voiceprint’s feature a

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Ssu-Min, Yang, and 楊斯閔. "Kernel-Based Fuzzy c-Means Clustering Algorithm Hadrware Implementation." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/72322960297601595511.

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