Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2017, Article ID 6129865, 14 pages
https://doi.org/10.1155/2017/6129865
Research Article

A Study on the Convergence of Family Particle Swarm Optimization

1Yuxi Normal University, Yuxi 653100, China
2Yunnan University, Yunnan 650091, China

Correspondence should be addressed to Zhenzhou An; moc.anis@uohznehzna

Received 31 August 2016; Revised 18 October 2016; Accepted 30 November 2016; Published 31 January 2017

Academic Editor: Bing Wang

Copyright © 2017 Zhenzhou An et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. Kennedy and R. Eberhart, “Particle swarm optimization,” in Proceedings of the IEEE International Conference on Neural Networks, pp. 1942–1948, Piscataway, NJ, USA, December 1995. View at Scopus
  2. S. Lahmiri and M. Boukadoum, “Combined partial differential equation filtering and particle swarm optimization for noisy biomedical image segmentation,” in Proceedings of the 7th IEEE Latin American Symposium on Circuits and Systems (LASCAS '16), pp. 363–366, Florianopolis, Brazil, March 2016. View at Publisher · View at Google Scholar · View at Scopus
  3. D. Ramyachitra, M. Sofia, and P. Manikandan, “Interval-value based particle swarm optimization algorithm for cancer-type specific gene selection and sample classification,” Genomics Data, vol. 5, pp. 46–50, 2015. View at Publisher · View at Google Scholar · View at Scopus
  4. R. J. Kuo, C. M. Chao, and Y. T. Chiu, “Application of particle swarm optimization to association rule mining,” Applied Soft Computing, vol. 11, no. 1, pp. 326–336, 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. T. Beielstein, K. E. Parsopoulos, and M. N. Vrahatis, “Tuning pso parameters through sensitivity analysis,” Technical Report, Reihe Computational Intelligence CI 124/02, Department of Computer Science, University of Dortmund, Dortmund, Germany, 2002. View at Google Scholar
  6. Y. Shi and R. C. Eberhart, “A modified particle swarm optimizer,” in Proceedings of the IEEE Congress on Evolutionary Computation, pp. 69–73, Piscataway, NJ, USA, 1998.
  7. I. C. Trelea, “The particle swarm optimization algorithm: convergence analysis and parameter selection,” Information Processing Letters, vol. 85, no. 6, pp. 317–325, 2003. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet · View at Scopus
  8. E. Ozcan and C. K. Mohan, “Analysis of a simple paticle swarm optimization system,” in Intelligent Engineering Systems through Artificial Neural Networks, pp. 253–258, 1998. View at Google Scholar
  9. E. Ozcan and C. K. Mohan, “Particle swarm optimization: Srufing the waves in,” in Proceedings of the 1999 Congress on Evolutionary Computation (CEC '99), Washington, DC, USA, 1999.
  10. F. Van Den Bergh and A. P. Engelbrecht, “A study of particle swarm optimization particle trajectories,” Information Sciences, vol. 176, no. 8, pp. 937–971, 2006. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  11. M. Clerc and J. Kennedy, “The particle swarm: explosion, stability, and convergence in a multidimensional complex space,” IEEE Transactions on Evolutionary Computation, vol. 6, no. 1, pp. 58–73, 2002. View at Publisher · View at Google Scholar · View at Scopus
  12. E. W. Burgess and H. J. Locke, The Family: From Institution to Companionship, American Book Company, New York, NY, USA, 1945.
  13. X. T. Fei, Shengyu zhidu (The Regime of Childbirth), Tianjin People's Publishing House, Tianjin, China, 1981.
  14. Z. Z. An, X. L. Shi, and J. H. Zhang, “Family particle swarm optimization,” in Proceedings of the 6th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM '10), IEEE, Chengdu, China, September 2010. View at Publisher · View at Google Scholar · View at Scopus
  15. Z. An, X. Shi, and J. Zhang, “A study on the internal structure of family particle swarm optimization,” in Proceedings of the 4th International Conference on Genetic and Evolutionary Computing (ICGEC '10), pp. 27–30, IEEE Computer Society, December 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. R. Mendes, Population Topologies and Their Influence in Particle Swarm Performance, University of Minho, 2004.