DocumentCode
1563941
Title
A new weighting fuzzy c-means algorithm
Author
Yu, Jian ; Houkuan Huang
Author_Institution
Dept. of Comput. Sci. & Technol., Northern Jiao Tong Univ., Beijing, China
Volume
2
fYear
2003
Firstpage
896
Abstract
It is always supposed that each cluster has almost equal number of points when carrying out the FCM. However, this assumption may not hold in practice. In this paper, we propose a novel fuzzy c-means algorithm based on the definition of generalized mean, weighting fuzzy c-means algorithms (WFCM). Noticing that the Gath-Geva fuzzy clustering algorithm considers the size of the clusters, we compare the performance between the WFCM and the Gath-Geva fuzzy clustering algorithms by numerical experiments. Moreover, we offer a theoretical threshold to choose an appropriate weighting exponent in the WFCM, which is also valid for the FCM, the numeric experiments verify such conclusion.
Keywords
fuzzy logic; fuzzy set theory; generalisation (artificial intelligence); pattern clustering; Gath-Geva fuzzy clustering algorithm; numerical experiments; performance evaluation; weighting exponent; weighting fuzzy c means algorithm; Algorithm design and analysis; Clustering algorithms; Computer science; Equations; Image analysis; Image databases; Image processing; Image recognition; Process design; Spatial databases;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
Print_ISBN
0-7803-7810-5
Type
conf
DOI
10.1109/FUZZ.2003.1206550
Filename
1206550
Link To Document