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The K-means clustering algorithm based on density and ant colony

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3 Author(s)
Peng Yuqing ; Sch. of Comput. Sci. & Eng., Hebei Univ. of Technol., Tianjin, China ; Hou Xiangdan ; Liu Shang

The ant algorithm is a new evolutional method, k-means and the density-cluster are familiar cluster analysis. In this paper, we proposed a new K-means algorithm based on density and ant theory, which resolved the problem of local minimal by the random of ants and handled the initial parameter sensitivity of k-means. In addition it combined idea of density and made the ants searching selectable. With the experiments it was proved that the algorithm we proposed improved the efficiency and precision of cluster.

Published in:

Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on  (Volume:1 )

Date of Conference:

14-17 Dec. 2003