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PR
2002
134views more  PR 2002»
13 years 4 months ago
Interactive clustering and merging with a new fuzzy expected value
7 Major problems exist in both crisp and fuzzy clustering algorithms. The fuzzy c-means type of algorithms use weights determined by a power m of inverse distances that remains
Carl G. Looney
PR
2006
84views more  PR 2006»
13 years 4 months ago
Geometric visualization of clusters obtained from fuzzy clustering algorithms
Fuzzy-clustering methods, such as fuzzy k-means and Expectation Maximization, allow an object to be assigned to multiple clusters with different degrees of membership. However, th...
Luis Rueda, Yuanquan Zhang
CEC
2007
IEEE
13 years 11 months ago
MRI brain image segmentation by fuzzy symmetry based genetic clustering technique
—In this paper, an automatic segmentation technique of multispectral magnetic resonance image of the brain using a new fuzzy point symmetry based genetic clustering technique is ...
Sriparna Saha, Sanghamitra Bandyopadhyay
AGENTS
2001
Springer
13 years 9 months ago
A fuzzy model of reputation in multi-agent systems
Agents are intended to interact in open systems where the knowledge about others (reputation) is incomplete and uncertain. Also, this knowledge about other agents is subjective si...
Javier Carbo Rubiera, José M. Molina L&oacu...
SSDBM
2005
IEEE
159views Database» more  SSDBM 2005»
13 years 10 months ago
Clustering Moving Objects via Medoid Clusterings
Modern geographic information systems do not only have to handle static information but also dynamically moving objects. Clustering algorithms for these moving objects provide new...
Hans-Peter Kriegel, Martin Pfeifle