• DocumentCode
    2559429
  • Title

    Soft sensor modeling of melt-index of High Pressure Low-Density Polyethylene

  • Author

    Bu Yan-ping ; Yu Jin-shou

  • Author_Institution
    Res. Inst. of Autom., East China Univ. of Sci. & Technol., Shanghai
  • fYear
    2008
  • fDate
    2-4 July 2008
  • Firstpage
    1818
  • Lastpage
    1822
  • Abstract
    On the basis of analyzing the particle swarm optimization (PSO) algorithm and support vector machine (SVM), the PSO algorithm with chaos searching is applied to optimize the parameters of SVM, then the PSO-SVM model about a practical soft-sensor of melt-index of high pressure low-density polyethylene is constructed. The method takes advantages of the minimum structure risk of SVM and the quickly globally optimizing ability of PSO for soft sensor modeling. The simulation results demonstrate that the model has effective generalization performance, higher precision and engineering practicability.
  • Keywords
    chemical engineering computing; particle swarm optimisation; polymer melts; sensors; support vector machines; chaos searching; high pressure low-density polyethylene; melt-index; particle swarm optimization; soft sensor modeling; support vector machine; Algorithm design and analysis; Automation; Chaos; Lagrangian functions; Logistics; Optimization methods; Particle swarm optimization; Polyethylene; Support vector machines; chaos; melt-index; particle swarm optimization algorithm; soft-sensor; support vector machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2008. CCDC 2008. Chinese
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-1733-9
  • Electronic_ISBN
    978-1-4244-1734-6
  • Type

    conf

  • DOI
    10.1109/CCDC.2008.4597637
  • Filename
    4597637