IDEAS home Printed from https://ideas.repec.org/a/aio/manmar/vxivy2016i2p264-274.html
   My bibliography  Save this article

Predicting Of The Development Of The Enterprise By Using Neural Network Tools

Author

Listed:
  • Nataliia PARKHOMENKO

    (Simon Kuznets Kharkiv National University of Economics, Ukraine)

Abstract

This research focused on prediction of the state of the enterprise and the artificial neural network is selected as a prediction tool. The prediction performed through the use of the financial key indicators. In this paper we analysed the dynamics of the of financial indicators of the company of Luhansk region "Luganskteplovoz", Ukraine and for solving of financial state of enterprise we used the software Statistica Neural Networks.

Suggested Citation

  • Nataliia PARKHOMENKO, 2016. "Predicting Of The Development Of The Enterprise By Using Neural Network Tools," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, vol. 0(2), pages 264-274, November.
  • Handle: RePEc:aio:manmar:v:xiv:y:2016:i:2:p:264-274
    as

    Download full text from publisher

    File URL: http://mnmk.ro/documents/2016_02/9.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    prediction; artificial neural network; development of the enterprise; model of forecasting; financial indicators;
    All these keywords.

    JEL classification:

    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • M20 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - General

    Statistics

    Access and download statistics

    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:aio:manmar:v:xiv:y:2016:i:2:p:264-274. 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: Catalin Barbu (email available below). General contact details of provider: https://edirc.repec.org/data/fecraro.html .

    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.