IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-662-43871-8_87.html
   My bibliography  Save this book chapter

Steel Prices Index Prediction in China Based on BP Neural Network

In: Liss 2014

Author

Listed:
  • Zhishuo Liu

    (Beijing Jiaotong University)

  • Yongcong Wang

    (Beijing Jiaotong University)

  • Shuang Zhu

    (Beijing Jiaotong University)

  • Baopeng Zhang

    (Beijing Jiaotong University)

  • Lingyun Wei

    (Beijing University of Posts and Telecommunications)

Abstract

Steel prices index in China are effected by upstream and downstream of steel supply chain, so it is necessary for steel prices index prediction to conduct correlation analysis between steel prices index and it’s influence factors. These influence factors are selected as input factors and steel prices index as output factor to establish a BPNN model, then the model is applied to predict with influence factors data ranging from October 2011 to October 2013 and output factor data ranging from November 2011 to November 2013. The training relative error is 0.32 %, and the prediction error is 6.8 %.The results prove BPNN has good predictive ability.

Suggested Citation

  • Zhishuo Liu & Yongcong Wang & Shuang Zhu & Baopeng Zhang & Lingyun Wei, 2015. "Steel Prices Index Prediction in China Based on BP Neural Network," Springer Books, in: Zhenji Zhang & Zuojun Max Shen & Juliang Zhang & Runtong Zhang (ed.), Liss 2014, edition 127, pages 603-608, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-43871-8_87
    DOI: 10.1007/978-3-662-43871-8_87
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kuo-Kun Tseng & Regina Fang-Ying Lin & Hongfu Zhou & Kevin Jati Kurniajaya & Qianyu Li, 2018. "Price prediction of e-commerce products through Internet sentiment analysis," Electronic Commerce Research, Springer, vol. 18(1), pages 65-88, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-662-43871-8_87. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.