Research on Hybrid Clustering Based on Density and Ant Colony Algorithm

This paper presents a hybrid clustering algorithm based on density and ant colony algorithm, that to determine the initial cluster centers according to cluster objects distribution density method, and then use the swarm intelligence and randomness of ant colony algorithm to find that arbitrary shape of clusters, to avoid falling into local convergence, to get a relatively stable global optimal solution. Theoretical analysis and experimental results show that the improved algorithm can achieve better clustering results.