DocumentCode :
1750769
Title :
Advanced mountain clustering method
Author :
Lee, Jung W. ; Son, Seo H. ; Kwon, Soon H.
Author_Institution :
Dept. of Electr. Eng., Yeungnam Univ., Kyongbuk, South Korea
Volume :
1
fYear :
2001
fDate :
25-28 July 2001
Firstpage :
275
Abstract :
We introduce the advanced mountain clustering method (AMM), which uses a normalized data space, a Gaussian type mountain function and a destruction method based on a mountain slope. The proposed method is very useful because it needs just one parameter instead of three in the mountain method of Yager and Filev (1994) and finds out cluster centers without any neighboring parasitic cluster centers. In addition, we propose a noniterative selection method for the only parameter ω. Finally, computer simulation results on numerical examples are presented to show the validity of the proposed clustering method
Keywords :
Gaussian processes; fuzzy logic; pattern clustering; AMM; FCM; Gaussian type mountain function; advanced mountain clustering method; cluster centers; destruction method; fuzzy C-means; fuzzy clustering methods; noniterative selection method; normalized data space; Clustering methods; Computer simulation; Control systems; Decision making; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Linearity; Pattern recognition; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-7078-3
Type :
conf
DOI :
10.1109/NAFIPS.2001.944264
Filename :
944264
Link To Document :
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