• DocumentCode
    690347
  • Title

    Prediction of Market Demand Based on AdaBoost_BP Neural Network

  • Author

    Song Li ; Jing Wang ; Bo Liu

  • Author_Institution
    Sch. of Manage., Hebei Univ., Baoding, China
  • fYear
    2013
  • fDate
    14-15 Dec. 2013
  • Firstpage
    305
  • Lastpage
    308
  • Abstract
    Aiming at the disadvantages of prediction model of single BP neural network, a prediction model was presented by combining AdaBoost algorithm and BP neural network for improving the forecasting accuracy of single BP neural network. The ensemble BP network based on AdaBoost is used as intelligent algorithm. Overcoming the instability of single BP neural network, the proposed models can give more accurate and stable prediction for the novel conditions. The main influence factors for prediction of market demand of refrigerator are analyzing detailed and used as the inputs of proposed prediction model. The efficiency of the proposed prediction model was tested by simulation of the market demand statistical data of a refrigerator enterprise in China. The simulation results have shown that the higher accuracy is expressed in this proposed model, and it is applicable to practice.
  • Keywords
    backpropagation; digital simulation; marketing; neural nets; refrigerators; statistical analysis; AdaBoost_BP neural network; ensemble BP network; intelligent algorithm; market demand statistical data simulation; refrigerator market demand prediction; single BP neural network; Accuracy; Biological neural networks; Forecasting; Prediction algorithms; Predictive models; Training; AdaBoost algorithm; BP neural networ; prediction of market demand;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Sciences and Applications (CSA), 2013 International Conference on
  • Conference_Location
    Wuhan
  • Type

    conf

  • DOI
    10.1109/CSA.2013.77
  • Filename
    6835604