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

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.