• DocumentCode
    2121088
  • Title

    The ant system-genetic algorithm particle filter

  • Author

    Juan, Zhao ; Li, Dong-feng

  • Author_Institution
    College of Mathematics and Information Sciences, North China University of Water Resources and Electric Power, Zhengzhou, China
  • fYear
    2010
  • fDate
    4-6 Dec. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Particle filter is a statistic filtering method based on sequential simulation. It has an outstanding contribution to the nonlinear non-Gaussian dynamic system. But how to choose particle probability distributing function and deal with particle degeneration is the key to the algorithm. A new evolutional algorithm called ant system is used during the iterative recurrence of sequential important sampling. Furthermore, the particle diversity was great increased by the using of genetic across, aberrance and selection. Simulation results show that this evolutional is better than traditional particle filter in the average absolute error and variance within a short time.
  • Keywords
    Algorithm design and analysis; Approximation algorithms; Heuristic algorithms; Markov processes; Particle filters; Prediction algorithms; Probability distribution; Ant System; Genetic Algorithm; Particle Degeneration; Particle Filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2010 2nd International Conference on
  • Conference_Location
    Hangzhou, China
  • Print_ISBN
    978-1-4244-7616-9
  • Type

    conf

  • DOI
    10.1109/ICISE.2010.5690150
  • Filename
    5690150