A Weighting Fuzzy Clustering Algorithm Based on Euclidean Distance

Considering a user's actual demand, this paper analyzed the functional requirments which can be brought forward by a user of a clustering system and proposed a fuzzy c-means clustering algorithm based on Euclidean distance. In this algorithm, weights are directly appointed by a user or a domanial expert. Different weights show the distinction of the userpsilas recognition of different character criterion. Compared with the traditional fuzzy c-means clustering method, this algorithm can improve the clusteringpsilas flexibility and produce a more satisfactory clustering result.