• DocumentCode
    507981
  • Title

    Research on Structural Optimization Arithmetic of Uplift Device of a Sugarcane Harvester Based on Hopfield Neural Network

  • Author

    Hu, Yizhi ; Hu, Yingchun

  • Author_Institution
    Guangxi Qinglong Machine Manuf. Corp. Ltd., Guiping, China
  • Volume
    1
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    284
  • Lastpage
    288
  • Abstract
    The structural optimal problem of a sugarcane harvester was solved through the method combined with Hopfield Neural Network (NN) and Simulated Annealing (SA). The corresponding relationships between Neural Network and optimal problem were built, such as NN energy function and objective of optimal problem, NN evolving process and searching process of optimal design, NN equilibrium point and solution of optimal problem and so on. The improved castigatory operator was used to accelerate NN convergence. After 12 iterations, the constraints reached their boundary which showed the design resources could be used sufficiently and the whole optimal results could be received. It is proved to be an effective and reliable way to be used in engineering projects and a new idea in solving the structural optimal problems.
  • Keywords
    Hopfield neural nets; production engineering; simulated annealing; Hopfield neural network; castigatory operator; simulated annealing; structural optimization arithmetic; sugarcane harvester device; uplift device optimization; Circuits; Computer aided manufacturing; Computer networks; Design optimization; Digital arithmetic; Hopfield neural networks; Neural networks; Neurons; Optimization methods; Virtual manufacturing; Hopfield Neural Network; Simulated annealing; Structural optimization; whole optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2009. ICNC '09. Fifth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3736-8
  • Type

    conf

  • DOI
    10.1109/ICNC.2009.416
  • Filename
    5364371