Comparison between Fuzzy C-means clustering and Fuzzy Clustering Subtractive in urban air pollution

Author

Collazo-Cuevas, J.I. ; Aceves-Fernandez, M.A. ; Gorrostieta-Hurtado, E. ; Pedraza-Ortega, J.C. ; Sotomayor-Olmedo, A. ; Delgado-Rosas, M.

Author_Institution

Univ. del Valle de Mexico (UVM), Queretaro, Mexico

fYear

2010

fDate

22-24 Feb. 2010

Firstpage

174

Lastpage

179

Abstract

Clustering is generally associated with classification problem. In this contribution, the implementation of cluster estimation method as a basis of a fuzzy model identification algorithm has been developed. A comparison between two different clustering techniques is presented, Fuzzy C-means clustering and Fuzzy Clustering Subtractive. Also, an application in modeling the relationship between temperature, humidity and PM10 concentration in urban air pollution in Liverpool at northwest of England is presented.

Keywords

fuzzy set theory; pattern clustering; cluster estimation method; clustering techniques; fuzzy C-means clustering; fuzzy clustering subtractive; fuzzy model identification; urban air pollution; Air pollution; Clustering algorithms; Fuzzy control; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Humans; Mathematical model; Pattern recognition; Telecommunications; Fuzzy model identification; fuzzy c-means; fuzzy clustering subtractive;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics, Communications and Computer (CONIELECOMP), 2010 20th International Conference on

Conference_Location

Cholula

Print_ISBN

978-1-4244-5352-8

Electronic_ISBN

978-1-4244-5353-5

Type

conf

DOI

10.1109/CONIELECOMP.2010.5440772

Filename

5440772