Fuzzy Clustering Models and Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fuzzy Clustering Models and Applications write by Mika Sato. This book was released on 1997. Fuzzy Clustering Models and Applications available in PDF, EPUB and Kindle.
Fuzzy Clustering Models and Applications
Fuzzy Clustering Models and Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fuzzy Clustering Models and Applications write by Mika Sato. This book was released on 1997-09-17. Fuzzy Clustering Models and Applications available in PDF, EPUB and Kindle. 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.
Algorithms for Fuzzy Clustering
Algorithms for Fuzzy Clustering - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Algorithms for Fuzzy Clustering write by Sadaaki Miyamoto. This book was released on 2008-04-15. Algorithms for Fuzzy Clustering available in PDF, EPUB and Kindle. 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.
Advances in Fuzzy Clustering and its Applications
Advances in Fuzzy Clustering and its Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advances in Fuzzy Clustering and its Applications write by Jose Valente de Oliveira. This book was released on 2007-06-13. Advances in Fuzzy Clustering and its Applications available in PDF, EPUB and Kindle. 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.
Fuzzy Sets & their Application to Clustering & Training
Fuzzy Sets & their Application to Clustering & Training - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fuzzy Sets & their Application to Clustering & Training write by Beatrice Lazzerini. This book was released on 2000-03-24. Fuzzy Sets & their Application to Clustering & Training available in PDF, EPUB and Kindle. 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.
