Aiming at problem that clustering result of fuzzy C-means（ FCM） clustering algorithm depends on selection of initial center

easy convergence to local minima

a hybrid clustering method combines density peak fast search algorithm（ DPC） with FCM algorithm（ DPC-FCM） is proposed. Algorithm uses DPC algorithm can accurately describe characteristics of initial cluster centers

to improve the shortcomings of the FCM clustering algorithm

so as to realize the optimization of clustering. The experimental results of the UCI data sets and artificial data sets show that the fused new algorithm has a higher accuracy and faster convergence speed

than traditional FCM algorithm thus proves the feasibility of the new algorithm.