IDEAS home Printed from https://ideas.repec.org/a/arp/ijefrr/2015p6-12.html
   My bibliography  Save this article

Forecasting Iron Price by Hybrid Intelligent System

Author

Listed:
  • Vida Varahrami

    (Assistant Professor of University of Shahid Beheshti, Iran)

Abstract

Novel hybrid intelligent framework is introduces by integration of GMDH neural networks with Web -based Text Mining (WTM) and GA and Rule-based Exert System (RES) in this paper for forecast iron price. Our research reveals that by employing hybrid intelligent fr amework for iron price forecasting, there is better forecasting results respect to the GMDH neural networks. Therefore significance of this study is to survey a hybrid intelligent framework for iron price forecasting.

Suggested Citation

  • Vida Varahrami, 2015. "Forecasting Iron Price by Hybrid Intelligent System," International Journal of Economics and Financial Research, Academic Research Publishing Group, vol. 1(1), pages 6-12, 04-2015.
  • Handle: RePEc:arp:ijefrr:2015:p:6-12
    as

    Download full text from publisher

    File URL: http://www.arpgweb.com/pdf-files/IJEFR1(1)6-12.pdf
    Download Restriction: no

    File URL: http://www.arpgweb.com/?ic=journal&journal=5&month=04-2015&issue=1&volume=1
    Download Restriction: no
    ---><---

    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:arp:ijefrr:2015:p:6-12. 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: Managing Editor (email available below). General contact details of provider: http://www.arpgweb.com/?ic=journal&journal=5&info=aims .

    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.