Fuzzy Clustering Models And Applications
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Fuzzy Clustering Models And Applications
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Author : Mika Sato
language : en
Publisher:
Release Date : 1997
Fuzzy Clustering Models And Applications written by Mika Sato and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with categories.
Fuzzy Clustering Models And Applications
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Author : Mika Sato
language : en
Publisher: Physica
Release Date : 1997-09-17
Fuzzy Clustering Models And Applications written by Mika Sato and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-09-17 with Business & Economics categories.
This book presents our most recent research on fuzzy clustering models and applications. These models represent new methods in the field of cluster analysis which are based on common properties between objects to be clustered. We present asymmetric aggregation operators as a new concept for representing asymmetric relationship between objects. Asymmetric aggregation operators are proposed in order to obtain clusters in which objects are not only similar to each other but are also asymetrically related. Implementation of clustering model by using neural networks is also presented. A number of examples are presented to demonstrate the proposed new techniques. This book will prove useful to the researchers, scientists, engineers and postgraduate students in all the areas including science, engineering and business.
Advances In Fuzzy Clustering And Its Applications
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Author : Jose Valente de Oliveira
language : en
Publisher: John Wiley & Sons
Release Date : 2007-06-13
Advances In Fuzzy Clustering And Its Applications written by Jose Valente de Oliveira and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-13 with Technology & Engineering categories.
A comprehensive, coherent, and in depth presentation of the state of the art in fuzzy clustering. Fuzzy clustering is now a mature and vibrant area of research with highly innovative advanced applications. Encapsulating this through presenting a careful selection of research contributions, this book addresses timely and relevant concepts and methods, whilst identifying major challenges and recent developments in the area. Split into five clear sections, Fundamentals, Visualization, Algorithms and Computational Aspects, Real-Time and Dynamic Clustering, and Applications and Case Studies, the book covers a wealth of novel, original and fully updated material, and in particular offers: a focus on the algorithmic and computational augmentations of fuzzy clustering and its effectiveness in handling high dimensional problems, distributed problem solving and uncertainty management. presentations of the important and relevant phases of cluster design, including the role of information granules, fuzzy sets in the realization of human-centricity facet of data analysis, as well as system modelling demonstrations of how the results facilitate further detailed development of models, and enhance interpretation aspects a carefully organized illustrative series of applications and case studies in which fuzzy clustering plays a pivotal role This book will be of key interest to engineers associated with fuzzy control, bioinformatics, data mining, image processing, and pattern recognition, while computer engineers, students and researchers, in most engineering disciplines, will find this an invaluable resource and research tool.
Algorithms For Fuzzy Clustering
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Author : Sadaaki Miyamoto
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-04-15
Algorithms For Fuzzy Clustering written by Sadaaki Miyamoto and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-15 with Computers categories.
Recently many researchers are working on cluster analysis as a main tool for exploratory data analysis and data mining. A notable feature is that specialists in di?erent ?elds of sciences are considering the tool of data clustering to be useful. A major reason is that clustering algorithms and software are ?exible in thesensethatdi?erentmathematicalframeworksareemployedinthealgorithms and a user can select a suitable method according to his application. Moreover clusteringalgorithmshavedi?erentoutputsrangingfromtheolddendrogramsof agglomerativeclustering to more recent self-organizingmaps. Thus, a researcher or user can choose an appropriate output suited to his purpose,which is another ?exibility of the methods of clustering. An old and still most popular method is the K-means which use K cluster centers. A group of data is gathered around a cluster center and thus forms a cluster. The main subject of this book is the fuzzy c-means proposed by Dunn and Bezdek and their variations including recent studies. A main reasonwhy we concentrate on fuzzy c-means is that most methodology and application studies infuzzy clusteringusefuzzy c-means,andfuzzy c-meansshouldbe consideredto beamajortechniqueofclusteringingeneral,regardlesswhetheroneisinterested in fuzzy methods or not. Moreover recent advances in clustering techniques are rapid and we requirea new textbook that includes recent algorithms.We should also note that several books have recently been published but the contents do not include some methods studied herein.
Fuzzy Sets Their Application To Clustering Training
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Author : Beatrice Lazzerini
language : en
Publisher: CRC Press
Release Date : 2000-03-24
Fuzzy Sets Their Application To Clustering Training written by Beatrice Lazzerini and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-03-24 with Computers categories.
Fuzzy set theory - and its underlying fuzzy logic - represents one of the most significant scientific and cultural paradigms to emerge in the last half-century. Its theoretical and technological promise is vast, and we are only beginning to experience its potential. Clustering is the first and most basic application of fuzzy set theory, but forms the basis of many, more sophisticated, intelligent computational models, particularly in pattern recognition, data mining, adaptive and hierarchical clustering, and classifier design. Fuzzy Sets and their Application to Clustering and Training offers a comprehensive introduction to fuzzy set theory, focusing on the concepts and results needed for training and clustering applications. It provides a unified mathematical framework for fuzzy classification and clustering, a methodology for developing training and classification methods, and a general method for obtaining a variety of fuzzy clustering algorithms. The authors - top experts from around the world - combine their talents to lay a solid foundation for applications of this powerful tool, from the basic concepts and mathematics through the study of various algorithms, to validity functionals and hierarchical clustering. The result is Fuzzy Sets and their Application to Clustering and Training - an outstanding initiation into the world of fuzzy learning classifiers and fuzzy clustering.
Innovations In Fuzzy Clustering
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Author : Mika Sato-Ilic
language : en
Publisher: Springer
Release Date : 2006-10-31
Innovations In Fuzzy Clustering written by Mika Sato-Ilic and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-10-31 with Mathematics categories.
This book presents the most recent advances in fuzzy clustering techniques and their applications. The contents include Introduction to Fuzzy Clustering; Fuzzy Clustering based Principal Component Analysis; Fuzzy Clustering based Regression Analysis; Kernel based Fuzzy Clustering; Evaluation of Fuzzy Clustering; Self-Organized Fuzzy Clustering. This book is directed to the computer scientists, engineers, scientists, professors and students of engineering, science, computer science, business, management, avionics and related disciplines.
Fuzzy Clustering Via Proportional Membership Model
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Author : Susana Nascimento
language : en
Publisher: IOS Press
Release Date : 2005
Fuzzy Clustering Via Proportional Membership Model written by Susana Nascimento and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.
Development of models with explicit mechanisms for data generation from cluster structures is of major interest in order to provide a theoretical framework for cluster structures found in data. Especially appealing in this regard are the so-called typological structures in which observed entities relate in various degrees to one or several prototypes. Such structures are relevant in many areas such as medicine or marketing, where any entity (patient/consumer) may adhere, with different degrees, to one or several prototypes (clinical scenario/consumer behavior), modelling a typological classification. In fuzzy clustering, the fuzzy c-means (FCM) method has become one of the most popular techniques. As a fuzzy analogue of c-means crisp clustering, FCM models a typological classification, much the same way as c-means. However, FCM does not adhere to the statistical paradigm at which the data are considered generated by a cluster structure, while crisp c-means does. The present work proposes a framework for typological classification based on a fuzzy clustering model of data generation.
Clustering And Fuzzy Techniques
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Author : Hizir
language : en
Publisher: Tenea Verlag Ltd.
Release Date : 2003
Clustering And Fuzzy Techniques written by Hizir and has been published by Tenea Verlag Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.
Model Identification Using Fuzzy Clustering And Applications
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Author : Eric Minh Nguyen
language : en
Publisher:
Release Date : 1998
Model Identification Using Fuzzy Clustering And Applications written by Eric Minh Nguyen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Automatic control categories.
Fuzzy Algorithms With Applications To Image Processing And Pattern Recognition
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Author : Zheru Chi
language : en
Publisher: World Scientific
Release Date : 1996-10-04
Fuzzy Algorithms With Applications To Image Processing And Pattern Recognition written by Zheru Chi and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-10-04 with Computers categories.
Contents:Introduction:Basic Concepts of Fuzzy SetsFuzzy RelationsFuzzy Models for Image Processing and Pattern RecognitionMembership Functions:IntroductionHeuristic SelectionsClustering ApproachesTuning of Membership FunctionsConcluding RemarksOptimal Image Thresholding:IntroductionThreshold Selection Based on Statistical Decision TheoryNon-fuzzy Thresholding AlgorithmsFuzzy Thresholding AlgorithmUnified Formulation of Three Thresholding AlgorithmsMultilevel ThresholdingApplicationsConcluding RemarksFuzzy Clustering:IntroductionC-Means AlgorithmFuzzy C-Means AlgorithmComparison between Hard and Fuzzy Clustering AlgorithmsCluster ValidityApplicationsConcluding RemarksLine Pattern Matching:IntroductionSimilarity Measures between Line SegmentsBasic Matching AlgorithmDealing with Noisy PatternsDealing with Rotated PatternsApplicationsConcluding RemarksFuzzy Rule-based Systems:IntroductionLearning from ExamplesDecision Tree ApproachFuzzy Aggregation Network ApproachMinimization of Fuzzy RulesDefuzzification and OptimizationApplicationsConcluding RemarksCombined Classifiers:IntroductionVoting SchemesMaximum Posteriori ProbabilityMultilayer Perceptron ApproachFuzzy Measures and Fuzzy IntegralsApplicationsConcluding Remarks Readership: Engineers and computer scientists. keywords: