Results 271 to 280 of about 2,884,172 (338)

Fuzzy Clustering: A Historical Perspective

IEEE Computational Intelligence Magazine, 2019
Fuzzy sets emerged in 1965 in a paper by Lotfi Zadeh. In 1969 Ruspini published a seminal paper that has become the basis of most fuzzy clustering algorithms.
E. Ruspini, J. Bezdek, J. Keller
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Fuzzy Clustering

2017
This chapter presents a study of the development of the clustering methodology to data analysis, with particular attention to the analysis from a crisp environment to a fuzzy environment. An applied problem concerning service quality (using SERVQUAL) of mobile phone users, and subsequent loyalty and satisfaction forms the data set to demonstrate the ...
Mashhour H. Baeshen, Malcolm J. Beynon, Kate L. Daunt   +2 more
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Dynamic fuzzy clustering using fuzzy cluster loading

International Journal of General Systems, 2006
When we obtain clusters through the classification of a given data it is important to interpret the meaning of the obtained clusters. This is particularly true in the clustering of 3-way asymmetric similarity data. This is true because the asymmetric property and the structure of similarity in each cluster are changed over the time periods (or ...
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From Soft Clustering to Hard Clustering: A Collaborative Annealing Fuzzy $c$-Means Algorithm

IEEE transactions on fuzzy systems
The fuzzy c-means clustering algorithm is the most widely used soft clustering algorithm. In contrast to hard clustering, the cluster membership of data generated using the fuzzy c-means algorithm is ambiguous.
Hongzong Li, Jun Wang
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Resource Assignment Based on Dynamic Fuzzy Clustering in Elastic Optical Networks With Multi-Core Fibers

IEEE Transactions on Communications, 2019
Space-division multiplexing elastic optical networks (SDM-EONs) will play an important role in addressing the increasing Internet traffic, thanks to their spectrum utilization flexibility and superior capacity. However, besides traditional physical layer
Hui Yang, Q. Yao, Ao Yu, Young Lee, Jie Zhang   +4 more
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Rough–Fuzzy Collaborative Clustering

IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2006
In this study, we introduce a novel clustering architecture, in which several subsets of patterns can be processed together with an objective of finding a common structure. The structure revealed at the global level is determined by exchanging prototypes of the subsets of data and by moving prototypes of the corresponding clusters toward each other ...
Sushmita, Mitra, Haider, Banka, Witold, Pedrycz   +2 more
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Context sensitive fuzzy clustering

18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397), 2003
We introduce an objective function-based fuzzy clustering technique that incorporates linear combinations of attributes in the distance function. The main application field of our method is image processing where a comparison pixel by pixel is usually not adequate, but the environment of a pixel or groups of pixels characterize important properties of ...
Keller, A., Klawonn, F.
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Sparse Representation-Based Intuitionistic Fuzzy Clustering Approach to Find the Group Intra-Relations and Group Leaders for Large-Scale Decision Making

IEEE transactions on fuzzy systems, 2019
In this paper, a sparse representation-based intuitionistic fuzzy clustering (SRIFC) approach is presented for solving the large-scale decision making (LSDM) problem.
Ru-Xi Ding, Xueqing Wang, Kun Shang, Bingsheng Liu, F. Herrera   +4 more
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Possibilistic Exponential Fuzzy Clustering

Journal of Computer Science and Technology, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Treerattanapitak, Kiatichai, Jaruskulchai, Chuleerat   +1 more
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Fuzzy clustering of mixed data

Information Sciences, 2019
A fuzzy clustering model for data with mixed features is proposed. The clustering model allows different types of variables, or attributes, to be taken into account.
P. D’Urso, Riccardo Massari
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