A New Hierarchical Clustering Algorithm on Fuzzy Data (FHCA)

134 Abstract—This paper presents a novel approach to cluster Fuzzy numbers using hierarchical method to be called (FHCA). In this approach a Dendrogram is drawn over fuzzy numbers until we could cluster fuzzy numbers using hierarchical cluster tree with inconsistency coefficient or other useful measures. All the similar previous methods extended FCM (Fuzzy Clustering Method) to support fuzzy data. On contrary, the present work is based on hierarchical method, i.e., we extended the hierarchical clustering algorithm to cluster fuzzy data for the first time. Finally this approach has been compared with some of the newly presented methods in the literature. The major advantage of the algorithm is its fault tolerance against noisy samples.