Clustering And Fuzzy Techniques

Author : Sadaaki Miyamoto,Hidetomo Ichihashi,Katsuhiro Honda
Publisher : Springer Science & Business Media
Page : 252 pages
File Size : 53,6 Mb
Release : 2008-04-15
Category : Computers
ISBN : 9783540787365

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Algorithms for Fuzzy Clustering by Sadaaki Miyamoto,Hidetomo Ichihashi,Katsuhiro Honda Pdf

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.

Author : Frank Höppner,Frank Klawonn,Rudolf Kruse,Thomas Runkler
Publisher : John Wiley & Sons
Page : 308 pages
File Size : 48,6 Mb
Release : 1999-07-09
Category : Science
ISBN : 0471988642

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Fuzzy Cluster Analysis by Frank Höppner,Frank Klawonn,Rudolf Kruse,Thomas Runkler Pdf

Dieser Band konzentriert sich auf Konzepte, Algorithmen und Anwendungen des Fuzzy Clustering. In sich geschlossen werden Techniken wie das Fuzzy-c-Mittel und die Gustafson-Kessel- und Gath- und Gava-Algorithmen behandelt, wobei vom Leser keine Vorkenntnisse auf dem Gebiet von Fuzzy-Systemen erwartet werden. Durch anschauliche Anwendungsbeispiele eignet sich das Buch als Einführung für Praktiker der Datenanalyse, der Bilderkennung und der angewandten Mathematik. (05/99)

Author : Hizir
Publisher : Tenea Verlag Ltd.
Page : 170 pages
File Size : 50,9 Mb
Release : 2003
Category : Electronic
ISBN : 9783865040398

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Clustering and Fuzzy Techniques by Hizir Pdf

Author : VIGNESH RAMAMOORTHY H
Publisher : BookRix
Page : 95 pages
File Size : 50,7 Mb
Release : 2019-11-28
Category : Technology & Engineering
ISBN : 9783748722182

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Fuzzy C-mean Clustering using Data Mining by VIGNESH RAMAMOORTHY H Pdf

The goal of traditional clustering is to assign each data point to one and only one cluster. In contrast, fuzzy clustering assigns different degrees of membership to each point. The membership of a point is thus shared among various clusters. This creates the concept of fuzzy boundaries which differs from the traditional concept of well-defined boundaries. In hard clustering, data is divided into distinct clusters, where each data element belongs to exactly one cluster. In fuzzy clustering (also referred to as soft clustering), data elements can belong to more than one cluster, and associated with each element is a set of membership levels. These indicate the strength of the association between that data element and a particular cluster. Fuzzy clustering is a process of assigning these membership levels, and then using them to assign data elements to one or more clusters. This algorithm uses the FCM traditional algorithm to locate the centers of clusters for a bulk of data points. The potential of all data points is being calculated with respect to specified centers. The availability of dividing the data set into large number of clusters will slow the processing time and needs more memory size for the program. Hence traditional clustering should device the data to four clusters and each data point should be located in one specified cluster .Imprecision in data and information gathered from and about our environment is either statistical(e.g., the outcome of a coin toss is a matter of chance) or no statistical (e.g., “apply the brakes pretty soon”). Many algorithms can be implemented to develop clustering of data sets. Fuzzy C-mean clustering (FCM) is efficient and common algorithm. We are tuning this algorithm to get a solution for the rest of data point which omitted because of its farness from all clusters. To develop a high performance algorithm that sort and group data set in variable number of clusters to use this data in control and managing of those clusters.

Author : Mika Sato,Yoshiharu Sato,L. C. Jain
Publisher : Physica
Page : 140 pages
File Size : 43,7 Mb
Release : 1997-09-17
Category : Business & Economics
ISBN : STANFORD:36105019373534

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Fuzzy Clustering Models and Applications by Mika Sato,Yoshiharu Sato,L. C. Jain Pdf

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.

Author : Shusaku Tsumoto,Roman Slowiński,Jan Komorowski,Jerzy W. Grzymala-Busse
Publisher : Springer Science & Business Media
Page : 871 pages
File Size : 43,7 Mb
Release : 2004-05-21
Category : Computers
ISBN : 9783540221173

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Rough Sets and Current Trends in Computing by Shusaku Tsumoto,Roman Slowiński,Jan Komorowski,Jerzy W. Grzymala-Busse Pdf

In recent years rough set theory has attracted the attention of many researchers and practitioners all over the world, who have contributed essentially to its development and applications. Weareobservingagrowingresearchinterestinthefoundationsofroughsets, including the various logical, mathematical and philosophical aspects of rough sets. Some relationships have already been established between rough sets and other approaches, and also with a wide range of hybrid systems. As a result, rough sets are linked with decision system modeling and analysis of complex systems, fuzzy sets, neural networks, evolutionary computing, data mining and knowledge discovery, pattern recognition, machine learning, and approximate reasoning. In particular, rough sets are used in probabilistic reasoning, granular computing (including information granule calculi based on rough mereology), intelligent control, intelligent agent modeling, identi?cation of autonomous s- tems, and process speci?cation. Methods based on rough set theory alone or in combination with other - proacheshavebeendiscoveredwith awide rangeofapplicationsinsuchareasas: acoustics, bioinformatics, business and ?nance, chemistry, computer engineering (e.g., data compression, digital image processing, digital signal processing, p- allel and distributed computer systems, sensor fusion, fractal engineering), de- sion analysis and systems, economics, electrical engineering (e.g., control, signal analysis, power systems), environmental studies, informatics, medicine, mole- lar biology, musicology, neurology, robotics, social science, software engineering, spatial visualization, Web engineering, and Web mining.

Author : Yaochu Jin,Lipo Wang
Publisher : Springer Science & Business Media
Page : 336 pages
File Size : 45,9 Mb
Release : 2009-04-15
Category : Computers
ISBN : 9783540899679

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Fuzzy Systems in Bioinformatics and Computational Biology by Yaochu Jin,Lipo Wang Pdf

Biological systems are inherently stochastic and uncertain. Thus, research in bioinformatics, biomedical engineering and computational biology has to deal with a large amount of uncertainties. Fuzzy logic has shown to be a powerful tool in capturing different uncertainties in engineering systems. In recent years, fuzzy logic based modeling and analysis approaches are also becoming popular in analyzing biological data and modeling biological systems. Numerous research and application results have been reported that demonstrated the effectiveness of fuzzy logic in solving a wide range of biological problems found in bioinformatics, biomedical engineering, and computational biology. Contributed by leading experts world-wide, this edited book contains 16 chapters presenting representative research results on the application of fuzzy systems to genome sequence assembly, gene expression analysis, promoter analysis, cis-regulation logic analysis and synthesis, reconstruction of genetic and cellular networks, as well as biomedical problems, such as medical image processing, electrocardiogram data classification and anesthesia monitoring and control. This volume is a valuable reference for researchers, practitioners, as well as graduate students working in the field of bioinformatics, biomedical engineering and computational biology.

Author : Jose Valente de Oliveira,Witold Pedrycz
Publisher : John Wiley & Sons
Page : 454 pages
File Size : 45,6 Mb
Release : 2007-06-13
Category : Technology & Engineering
ISBN : 0470061189

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Advances in Fuzzy Clustering and its Applications by Jose Valente de Oliveira,Witold Pedrycz Pdf

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.

Author : Jose Valente de Oliveira,Witold Pedrycz
Publisher : John Wiley & Sons
Page : 464 pages
File Size : 51,5 Mb
Release : 2007-06-05
Category : Computers
ISBN : UOM:39015069315052

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Advances in Fuzzy Clustering and Its Applications by Jose Valente de Oliveira,Witold Pedrycz Pdf

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.

Author : Management Association, Information Resources
Publisher : IGI Global
Page : 1618 pages
File Size : 43,6 Mb
Release : 2020-02-07
Category : Technology & Engineering
ISBN : 9781799824558

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Sensor Technology: Concepts, Methodologies, Tools, and Applications by Management Association, Information Resources Pdf

Collecting and processing data is a necessary aspect of living in a technologically advanced society. Whether it’s monitoring events, controlling different variables, or using decision-making applications, it is important to have a system that is both inexpensive and capable of coping with high amounts of data. As the application of these networks becomes more common, it becomes imperative to evaluate their effectiveness as well as other opportunities for possible implementation in the future. Sensor Technology: Concepts, Methodologies, Tools, and Applications is a vital reference source that brings together new ways to process and monitor data and to put it to work in everything from intelligent transportation systems to healthcare to multimedia applications. It also provides inclusive coverage on the processing and applications of wireless communication, sensor networks, and mobile computing. Highlighting a range of topics such as internet of things, signal processing hardware, and wireless sensor technologies, this multi-volume book is ideally designed for research and development engineers, IT specialists, developers, graduate students, academics, and researchers.

Author : James C. Bezdek
Publisher : Springer Science & Business Media
Page : 267 pages
File Size : 50,9 Mb
Release : 2013-03-13
Category : Mathematics
ISBN : 9781475704501

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Pattern Recognition with Fuzzy Objective Function Algorithms by James C. Bezdek Pdf

The fuzzy set was conceived as a result of an attempt to come to grips with the problem of pattern recognition in the context of imprecisely defined categories. In such cases, the belonging of an object to a class is a matter of degree, as is the question of whether or not a group of objects form a cluster. A pioneering application of the theory of fuzzy sets to cluster analysis was made in 1969 by Ruspini. It was not until 1973, however, when the appearance of the work by Dunn and Bezdek on the Fuzzy ISODATA (or fuzzy c-means) algorithms became a landmark in the theory of cluster analysis, that the relevance of the theory of fuzzy sets to cluster analysis and pattern recognition became clearly established. Since then, the theory of fuzzy clustering has developed rapidly and fruitfully, with the author of the present monograph contributing a major share of what we know today. In their seminal work, Bezdek and Dunn have introduced the basic idea of determining the fuzzy clusters by minimizing an appropriately defined functional, and have derived iterative algorithms for computing the membership functions for the clusters in question. The important issue of convergence of such algorithms has become much better understood as a result of recent work which is described in the monograph.

Author : N. Kondruk
Publisher : Infinite Study
Page : 7 pages
File Size : 47,9 Mb
Release : 2024-06-15
Category : Electronic
ISBN : 8210379456XXX

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CLUSTERING METHOD BASED ON FUZZY BINARY RELATION by N. Kondruk Pdf

One of the most interesting and promising approaches to the analysis of multivariate phenomena and processes are methods of cluster analysis or automatic classification of objects. Clustering is one of the key areas of data mining. Its objective is identification of some unknown structure of a group of similar objects in the initial set.

Author : Z.-Q. Liu,S. Miyamoto
Publisher : Springer Science & Business Media
Page : 336 pages
File Size : 42,5 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9784431679073

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Soft Computing and Human-Centered Machines by Z.-Q. Liu,S. Miyamoto Pdf

Computer Science Workbench is a monograph series which will provide you with an in-depth working knowledge of current developments in computer technology. Every volume in this series will deal with a topic of importance in computer science and elaborate on how you yourself can build systems related to the main theme. You will be able to develop a variety of systems, including computer software tools, computer graphics, computer animation, database management systems, and computer-aided design and manufacturing systems. Computer Science Work bench represents an important new contribution in the field of practical computer technology. Tosiyasu L. Kunii Preface With the advent of digital computers some five decades ago and the wide spread use of computer networks recently, we have gained enormous power in gathering information and manufacturing. Yet, this increase in comput ing power has not given us freedom in a real sense, we are increasingly enslaved by the very machine we built for gaining freedom and efficiency. Making machines to serve mankind is an essential issue we are facing. Building human-centered systems is an imperative task for scientists and engineers in the new millennium. The topic of human-centered servant modules covers a vast area. In our projects we have focused our efforts on developing theories and techn!ques based on fuzzy theories. Chapters 2 to 12 in this book collectively deal with the theoretical, methodological, and applicational aspects of human centered systems. Each chapter presents the most recent research results by the authors on a particular topic.

Author : Cengiz Kahraman,Selcuk Cebi,Sezi Cevik Onar,Basar Oztaysi,A. Cagri Tolga,Irem Ucal Sari
Publisher : Springer Nature
Page : 954 pages
File Size : 54,7 Mb
Release : 2021-08-23
Category : Technology & Engineering
ISBN : 9783030856267

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Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation by Cengiz Kahraman,Selcuk Cebi,Sezi Cevik Onar,Basar Oztaysi,A. Cagri Tolga,Irem Ucal Sari Pdf

This book presents recent research in intelligent and fuzzy techniques. Emerging conditions such as pandemic, wars, natural disasters and various high technologies force people for significant changes in business and social life. The adoption of digital technologies to transform services or businesses, through replacing non-digital or manual processes with digital processes or replacing older digital technology with newer digital technologies through intelligent systems is the main scope of this book. It focuses on revealing the reflection of digital transformation in our business and social life under emerging conditions through intelligent and fuzzy systems. The latest intelligent and fuzzy methods and techniques on digital transformation are introduced by theory and applications. The intended readers are intelligent and fuzzy systems researchers, lecturers, M.Sc. and Ph.D. students studying digital transformation. Usage of ordinary fuzzy sets and their extensions, heuristics and metaheuristics from optimization to machine learning, from quality management to risk management makes the book an excellent source for researchers.

Author : Susana Nascimento
Publisher : IOS Press
Page : 204 pages
File Size : 50,6 Mb
Release : 2005
Category : Computers
ISBN : 1586034898

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Fuzzy Clustering Via Proportional Membership Model by Susana Nascimento Pdf

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.