Clustering Algorithm Based on Fuzzy C-means and Artificial Fish Swarm

Clustering algorithm has applied in many fields such as data mining, statistics and machine learning. But the clustering number and the initial clustering center affect the accuracy of clustering. In this paper, the average information entropy and density function are used to determine the clustering number and the initial clustering center respectively based on fuzzy C-means clustering algorithm. And then the new bionic optimization algorithm---artificial fish swarm is applied to cluster. Artificial fish swarm algorithm is simple and easy to implement. The experimental results show the efficiency of the proposed clustering algorithm. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Harbin University of Science and Technology