• DocumentCode
    2974163
  • Title

    Soft-sensor modeling of product particle size in ball milling circuits based on fuzzy neural networks with particle swarm optimization

  • Author

    Wu, Xinggang ; Yuan, Mingzhe

  • Author_Institution
    Key Lab. of Ind. Inf., Chinese Acad. of Sci., Shenyang, China
  • fYear
    2009
  • fDate
    22-24 June 2009
  • Firstpage
    1458
  • Lastpage
    1461
  • Abstract
    By combining particle swarm optimization algorithm (PSO) with fuzzy neural networks (FNN), a PSO fuzzy neural networks (PSO-FNN) was proposed. Then PSO-FNN was applied in soft-sensor modeling of product particle size in ball milling circuits. The new method assumed that FNN was used to construct the soft-sensor modeling of product particle size while PSO was employed to optimize parameters of FNN. Experiment results show that the model based on PSO-FNN has higher precision and better performance than the model based on BPNN.
  • Keywords
    ball milling; fuzzy neural nets; particle size; particle swarm optimisation; production engineering computing; sizing (materials processing); FNN; PSO; ball milling circuits; fuzzy neural network; particle swarm optimization; product particle size; soft-sensor modeling; Automation; Ball milling; Circuits; Fuzzy neural networks; Informatics; Optimization methods; Parameter estimation; Particle measurements; Particle swarm optimization; Size measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation, 2009. ICIA '09. International Conference on
  • Conference_Location
    Zhuhai, Macau
  • Print_ISBN
    978-1-4244-3607-1
  • Electronic_ISBN
    978-1-4244-3608-8
  • Type

    conf

  • DOI
    10.1109/ICINFA.2009.5205146
  • Filename
    5205146