Particle swarm optimization algorithm and its application to clustering analysis

@article{Chen2004ParticleSO,
  title={Particle swarm optimization algorithm and its application to clustering analysis},
  author={Ching-Yi Chen and Fun Ye},
  journal={2012 Proceedings of 17th Conference on Electrical Power Distribution},
  year={2004},
  pages={789-794}
}
Clustering analysis is applied generally to Pattern Recognition, Color Quantization and Image Classification. It can help the user to distinguish the structure of data and simplify the complexity of data from mass information. The user can understand the implied information behind extracting these data. In real case, the distribution of information can be any size and shape. A particle swarm optimization algorithm-based technique, called PSO-clustering, is proposed in this article. We adopt the… CONTINUE READING
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References

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Showing 1-7 of 7 references

Particle Swarm Optimization: Developments, Applications and Resources,

Russell C. Eberhart, Yuhui Shi
Proceedings of the IEEE Congress on Evolutionary Compufation (CEC ZOOI), Seoul, • 2001

Ksmeans type algorithms : a generalized convergence theorem and characterization of local optimality

R. C. Gonzalez J. T. TOll
Pattern Recognition Principles • 1974

Particle Swarm Optimization,

J. Kennedy, R. Eberhart
Proc. of IEEE international Conference on Neural Nehvorks (ICW), Vol.IV, pp • 1948

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