Data fitting via chaotic ant swarm

  • Authors:

  • Yu-Ying Li;Li-Xiang Li;Qiao-Yan Wen;Yi-Xian Yang

  • Affiliations:

  • School of Science, Beijing University of Posts and Telecommunications, Beijing, China;Information Security Center, Department of Information Engineering, Beijing University of Posts and Telecommunications, Beijing, China;School of Science, Beijing University of Posts and Telecommunications, Beijing, China;Information Security Center, Department of Information Engineering, Beijing University of Posts and Telecommunications, Beijing, China

  • Venue:
  • ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
  • Year:
  • 2006

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Abstract

A novel method of data fitting via chaotic ant swarm (CAS) is presented in this paper. Through the construction of a suitable function, the problem of data fitting can be viewed as that of parameter optimization, and then the CAS is used to search the parameter space so as to find the optimal estimations of the system parameters. To investigate the performances of the CAS, the CAS is compared with the particle swarm optimization (PSO) on two test problems. Simulation results indicate that the CAS achieves better performances.