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