Advances in Fuzzy Clustering and its Applications

Download or Read eBook Advances in Fuzzy Clustering and its Applications PDF written by Jose Valente de Oliveira and published by John Wiley & Sons. This book was released on 2007-06-13 with total page 454 pages. Available in PDF, EPUB and Kindle.
Advances in Fuzzy Clustering and its Applications
Author :
Publisher : John Wiley & Sons
Total Pages : 454
Release :
ISBN-10 : 0470061189
ISBN-13 : 9780470061183
Rating : 4/5 (89 Downloads)

Book Synopsis Advances in Fuzzy Clustering and its Applications by : Jose Valente de Oliveira

Book excerpt: 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.


Advances in Fuzzy Clustering and its Applications Related Books

Advances in Fuzzy Clustering and its Applications
Language: en
Pages: 454
Authors: Jose Valente de Oliveira
Categories: Technology & Engineering
Type: BOOK - Published: 2007-06-13 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

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
Algorithms for Fuzzy Clustering
Language: en
Pages: 252
Authors: Sadaaki Miyamoto
Categories: Computers
Type: BOOK - Published: 2008-04-15 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

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
Data Clustering: Theory, Algorithms, and Applications, Second Edition
Language: en
Pages: 430
Authors: Guojun Gan
Categories: Mathematics
Type: BOOK - Published: 2020-11-10 - Publisher: SIAM

DOWNLOAD EBOOK

Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the
Pattern Recognition with Fuzzy Objective Function Algorithms
Language: en
Pages: 267
Authors: James C. Bezdek
Categories: Mathematics
Type: BOOK - Published: 2013-03-13 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

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.
Recent Advances in Hybrid Metaheuristics for Data Clustering
Language: en
Pages: 196
Authors: Sourav De
Categories: Computers
Type: BOOK - Published: 2020-06-02 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

An authoritative guide to an in-depth analysis of various state-of-the-art data clustering approaches using a range of computational intelligence techniques Rec