• DocumentCode
    1633194
  • Title

    Research on the price prediction in supply chain based on data mining technology

  • Author

    Yang LanQin ; Xin, Xu

  • Volume
    2
  • fYear
    2012
  • Firstpage
    460
  • Lastpage
    463
  • Abstract
    Through using data mining methods, we can find useful hidden trends and relationships in the mass data. This can help supply chain companies to improve the quality of decision-making on supply chain management with the gained knowledge. Take the supply chain product polyester filament as an example, through the influence factor analysis of polyester filament price; this paper uses data mining methods to predict the prices of polyester filament. The established predictive models and analytical results can be used in the supply chain enterprises and as the basis of macro-control on the chemical fiber industry of and relevant departments.
  • Keywords
    data mining; decision making; forecasting theory; plastics industry; polymer fibres; pricing; production planning; supply chain management; chemical fiber industry; data mining technology; decision making; polyester filament price prediction; predictive models; supply chain product polyester filament; Chemicals; Data mining; Data models; Forecasting; Predictive models; Supply chains; Data Mining; Price Prediction; Supply Chain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation & Measurement, Sensor Network and Automation (IMSNA), 2012 International Symposium on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4673-2465-6
  • Type

    conf

  • DOI
    10.1109/MSNA.2012.6324621
  • Filename
    6324621