• DocumentCode
    120288
  • Title

    A Novel Forecasting Method for Large-Scale Sales Prediction Using Extreme Learning Machine

  • Author

    Ming Gao ; Wei Xu ; Hongjiao Fu ; Mingming Wang ; Xun Liang

  • Author_Institution
    Sch. of Inf., Renmin Univ. of China, Beijing, China
  • fYear
    2014
  • fDate
    4-6 July 2014
  • Firstpage
    602
  • Lastpage
    606
  • Abstract
    With the rise of e-commerce business, sales forecasting plays an increasingly important role, for accurate and speedy forecasting can help e-commerce companies solve all the uncertainty associated with demand and supply and reduce inventory cost. As the rapid growth in the amount of data, traditional intelligence models like Neural Networks have weakness in terms of speed. In this paper, we introduce the algorithm of ELM (extreme learning machine). In addition, we subjoin many e-commerce related indicators to increase the accuracy and reliability of prediction. In sum, the new model provides a better result both in terms of speed and accuracy. Experiments are conducted with the real sales data from an e-commerce company in China.
  • Keywords
    electronic commerce; forecasting theory; learning (artificial intelligence); retail data processing; sales management; China e-commerce company; demand and supply; e-commerce business; extreme learning machine; forecasting method; intelligence models; inventory cost reduction; large-scale sales prediction; sales forecasting; Accuracy; Books; Companies; Educational institutions; Forecasting; Predictive models; Training; E-commerce; ELM Algorithm; Sales prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Sciences and Optimization (CSO), 2014 Seventh International Joint Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-5371-4
  • Type

    conf

  • DOI
    10.1109/CSO.2014.116
  • Filename
    6923757