• DocumentCode
    530614
  • Title

    The costs prediction of AOD furnace based on improved RBF neural network

  • Author

    Na, Tang ; De-jiang, Zhang ; Hui, Li

  • Author_Institution
    Changchun Inst. of Opt., Fine Mech. & Phys., Grad. Univ. of Chinese Acad. of Sci., Changchun, China
  • Volume
    4
  • fYear
    2010
  • fDate
    24-26 Aug. 2010
  • Firstpage
    523
  • Lastpage
    526
  • Abstract
    In order to predict the cost, a model of cost prediction was set up based on adaptive hierarchical genetic algorithm and RBF neural network. Hierarchical genetic algorithm could optimize the topology and the parameters simultaneously. Compared with simple genetic algorithm, it has more efficiency in not only accelerating and stabilizing the parameters training but also determining the structure of the network. Adaptive crossover and mutation probability could accelerate the speed and avoid prematurity. The model was tested by five samples. The results showed that the prediction model has high prediction accuracy, which indicated that it was applicable to predict the cost by the model.
  • Keywords
    costing; furnaces; genetic algorithms; radial basis function networks; topology; AOD furnace; RBF neural network; adaptive hierarchical genetic algorithm; cost prediction; radial basis function neural network; Furnaces; Genetics; Legged locomotion; Predictive models; AOD furnace; RBF neural network; adaptive hierarchical genetic algorithm; cost prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
  • Conference_Location
    Changchun
  • Print_ISBN
    978-1-4244-7957-3
  • Type

    conf

  • DOI
    10.1109/CMCE.2010.5610089
  • Filename
    5610089