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Informationen zum Autor José Valente de Oliveira received his Ph.D. (1996), M.Sc. (1992), and the "Licenciado" degree in Electrical and Computer Engineering from the IST, Technical University of Lisbon. Currently he is an Assistant Professor in the Faculty of Science and Technology at the University of Algarve where he served as Deputy Dean from 2002-2003. He was recently appointed director of the University of Algarve Informatics Lab, a research laboratory specializing in computational intelligence including fuzzy sets, fuzzy and intelligent systems, machine learning, and optimization. Witold Pedrycz is a Professor and Canada Research Chair (CRC) in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences. He is actively pursuing research in computational intelligence, fuzzy modeling, knowledge discovery and data mining, fuzzy control including fuzzy controllers, pattern recognition, knowledge-based neural networks, relational computation, bioinformatics, and Software Engineering. He currently serves as an Associate Editor of IEEE Transactions on Fuzzy Systems. Klappentext 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 roleThis 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. Zusammenfassung Divided into four sections, Advances in Fuzzy Clustering and its Applications first explores the essentials of fuzzy clustering, including motivation, basic algorithms, computing aspects, realizations, cluster validity assessment, and ensuing interpretation of the results along with several representative areas of applications. Inhaltsverzeichnis List of Contributors xi Foreword xv Preface xvii Part I Fundamentals 1 1 Fundamentals of Fuzzy Clustering 3 Rudolf Kruse, Christian Döring and Marie-Jeanne Lesot 1.1 Introduction 3 1.2 Basic Clustering Algorithms 4 1.3 Distance Function Variants 14 1.4 Objective Function Variants 18 1.5 Update Equation Variants: Alternating Cluster Estimation 25 1.6 Concluding Remarks 27 Acknowledgements 28 References 29 2 Relational Fuzzy Clustering 31 Thomas A. Runkler 2.1 Introduction 31 2.2 Object and Relational Data 31 2.3 Object Data Clustering Models 34...
