The Research on Demand Forecasting of Supply Chain Based on ICCELMAN

نویسندگان

  • Peiyu Ren
  • Yancang Li
  • Huiping Song
  • Ning Lei
چکیده

Under the background of the globalization, the competition among the enterprises becomes more and more fierce. And the speed of the product circulation is faster than before. Under this background, if the company forecasts the product demand more accurate, the company can plan the product planning according to the demand. The companies can improve the competitiveness. In this paper, we apply the chaotic forecasting theory to forecast the product demand. Aiming at the defect of the traditional c-c method, we combine the Elam neural network model and put forward a new forecasting method. The method is ICCELMAN. We apply this method to forecast the product demand. Finally, the numerical analysis results show that the method can forecast the trended fluctuation for the actual demand accurately. The method has good forecasting accuracy.

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تاریخ انتشار 2016