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FUZZIEEE
2007
IEEE
14 years 2 months ago
Adaptive Optimization of the Number of Clusters in Fuzzy Clustering
In this paper, we present a local, adaptive optimization scheme for adjusting the number of clusters in fuzzy C-means clustering. This method is especially motivated by online app...
Jürgen Beringer, Eyke Hüllermeier
FSKD
2005
Springer
95views Fuzzy Logic» more  FSKD 2005»
14 years 1 months ago
The Fuzzy Mega-cluster: Robustifying FCM by Scaling Down Memberships
A new robust clustering scheme based on fuzzy c-means is proposed and the concept of a fuzzy mega-cluster is introduced in this paper. The fuzzy mega-cluster is conceptually simila...
Amit Banerjee, Rajesh N. Davé
FUZZIEEE
2007
IEEE
14 years 8 days ago
Evolving Single- and Multi-Model Fuzzy Classifiers with FLEXFIS-Class
Abstract-- In this paper a new method for training singlemodel and multi-model fuzzy classifiers incrementally and adaptively is proposed, which is called FLEXFIS-Class. The evolvi...
Edwin Lughofer, Plamen P. Angelov, Xiaowei Zhou
FUZZIEEE
2007
IEEE
14 years 2 months ago
Prototype-less Fuzzy Clustering
Abstract—In contrast to standard fuzzy clustering, which optimizes a set of prototypes, one for each cluster, this paper studies fuzzy clustering without prototypes. Starting fro...
Christian Borgelt
AINA
2005
IEEE
14 years 2 months ago
A CAC Scheme for Multimedia Applications Based on Fuzzy Logic
The purpose of admission control is to support the Quality of Service (QoS) demands of real time applications via resource reservation. In order to deal with admission control for...
Leonard Barolli, Mimoza Durresi, Kaoru Sugita, Arj...