• DocumentCode
    3733810
  • Title

    Research on Test Paper Auto-generating Based on Improved Particle Swarm Optimization

  • Author

    Chong Zhang;Jing Zhang

  • Author_Institution
    Tianjin Polytech. Univ., Tianjin, China
  • fYear
    2015
  • Firstpage
    92
  • Lastpage
    96
  • Abstract
    The existing algorithm of generating test paper has the problem of low efficiency and slow convergence rate, etc. Improved particle swarm algorithm for test paper auto-generating is proposed on the basic of the particle swarm optimization algorithm and improved genetic algorithm. The algorithm uses greedy algorithm to optimize the initial population. The crossover and mutation operator of genetic algorithm are used to avoid the local convergence of population during the process of iteration. Experimental results show that the improved particle swarm optimization algorithm can applied to auto-generating test paper, which has faster speed and higher success rate.
  • Keywords
    "Parallel architectures","Programming"
  • Publisher
    ieee
  • Conference_Titel
    Parallel Architectures, Algorithms and Programming (PAAP), 2015 Seventh International Symposium on
  • ISSN
    2168-3042
  • Type

    conf

  • DOI
    10.1109/PAAP.2015.27
  • Filename
    7387307