• DocumentCode
    1709831
  • Title

    Optimization of feeding rate for alcohol fermentation by quantum-behaved Particle Swarm Optimization

  • Author

    Lu, Ke-zhong ; Li, Hai-bo ; Wang, Ru-chuan

  • Author_Institution
    Dept. of Comput. Sci., Chizhou Coll., Chizhou, China
  • fYear
    2010
  • Firstpage
    4677
  • Lastpage
    4680
  • Abstract
    Quantum-behaved Particle Swarm Optimization (QPSO) algorithm is a global convergence guaranteed search method, which introduced quantum theory into traditional Particle Swarm Optimization (PSO). QPSO algorithm outperforms traditional PSO algorithm in search ability as well as having less parameter. In this paper, we employ QPSO algorithm to optimize the feeding rate of alcohol fermentation with the data of alcohol fermentation process. The simulation results show that QPSO algorithm can find better feeding rate quickly and yield more 4% output than traditional PSO algorithm.
  • Keywords
    fermentation; particle swarm optimisation; QPSO algorithm; alcohol fermentation; convergence guaranteed search method; feeding rate optimization; quantum theory; quantum-behaved particle swarm optimization; Biological system modeling; Bioreactors; Computational modeling; Optimization; Particle swarm optimization; Production; alcohol fermentation; feeding optimization; quantum-behaved particle swarm optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2010 8th World Congress on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-4244-6712-9
  • Type

    conf

  • DOI
    10.1109/WCICA.2010.5555294
  • Filename
    5555294