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Generalized Fuzzy C-Means Clustering Algorithm With Improved Fuzzy Partitions
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2009The fuzziness index m has important influence on the clustering result of fuzzy clustering algorithms, and it should not be forced to fix at the usual value m = 2. In view of its distinctive features in applications and its limitation in having m = 2 only, a recent advance of fuzzy clustering called fuzzy c-means clustering with improved fuzzy ...
Lin, Zhu, Fu-Lai, Chung, Shitong, Wang
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IEEE transactions on fuzzy systems, 2022
Fuzzy $c$-means (FCM) clustering is a promising method to handle uncertainties in data clustering. However, the traditional FCM and most of its variants cannot address incomplete inputs.
Yan Song +4 more
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Fuzzy $c$-means (FCM) clustering is a promising method to handle uncertainties in data clustering. However, the traditional FCM and most of its variants cannot address incomplete inputs.
Yan Song +4 more
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Wavelet Frame-Based Fuzzy C-Means Clustering for Segmenting Images on Graphs
IEEE Transactions on Cybernetics, 2020In recent years, image processing in a Euclidean domain has been well studied. Practical problems in computer vision and geometric modeling involve image data defined in irregular domains, which can be modeled by huge graphs.
Cong Wang +4 more
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Shadowed c-means: Integrating fuzzy and rough clustering
Pattern Recognition, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mitra, Sushmita +2 more
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Median fuzzy c-means for clustering dissimilarity data
Neurocomputing, 2010Median clustering is a powerful methodology for prototype based clustering of similarity/dissimilarity data. In this contribution we combine the median c-means algorithm with the fuzzy c-means approach, which is only applicable for vectorial (metric) data in its original variant.
Geweniger, T. +3 more
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Fuzzy C-means Clustering Algorithm for Cluster Membership Determination
International Journal of Advanced Engineering and Business Sciences, 2020Membership of open star clusters or Galactic open clusters is very important roles to study the formation and evaluation of gravitationally bound system. In the field of an image, the relative x and y coordinate positions of each star with respect to all the other stars are adapted. Therefore, in this paper, a new method for the determination open star
I. Selim, Mohamed Abd El Aziz
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Fuzzy C-means and fuzzy swarm for fuzzy clustering problem
Expert Systems with Applications, 2011Fuzzy clustering is an important problem which is the subject of active research in several real-world applications. Fuzzy c-means (FCM) algorithm is one of the most popular fuzzy clustering techniques because it is efficient, straightforward, and easy to implement.
Hesam Izakian, Ajith Abraham
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A Novel Type-2 Fuzzy C-Means Clustering for Brain MR Image Segmentation
IEEE Transactions on Cybernetics, 2020The fuzzy $C$ -means (FCM) clustering procedure is an unsupervised form of grouping the homogenous pixels of an image in the feature space into clusters. A brain magnetic resonance (MR) image is affected by noise and intensity inhomogeneity (IIH) during
P. Mishro +3 more
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Interval Type-2 Relative Entropy Fuzzy C-Means clustering
Information Sciences, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zarinbal, M. +2 more
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Parallel Fuzzy c-Means Cluster Analysis
2007This work presents an implementation of a parallel Fuzzy c-means cluster analysis tool, which implements both aspects of cluster investigation: the calculation of clusters' centers with the degrees of membership of records to clusters, and the determination of the optimal number of clusters for the data, by using the PBM validity index to evaluate the ...
Marta V. Modenesi +3 more
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