IDEAS home Printed from https://ideas.repec.org/a/idp/bizinf/y2014i1p69_73.html
   My bibliography  Save this article

Evolution Methods of Formation of Neuronet Models of Complex Economic Systems

Author

Listed:
  • Khemelyov Oleksandr H.

    (Donbas State Technical University)

Abstract

The article analyses principles of formation of neuronet models of complex economic systems. It justifies prospectiveness of use of artificial intellect methods when modelling complex economic systems. It shows a possibility of use of evolution methods when forming neuronet models of complex economic systems for ensuring invariance of their generalising properties. It offers an algorithm with a genome from operons of fixed length. It considers all operons from the point of view of functional positions. It notes a specific feature of the algorithm, which allows excluding anthropogenic factors when selecting the neuronet models architecture. It proves adequacy of the formed neuronet models of complex economic systems.

Suggested Citation

  • Khemelyov Oleksandr H., 2014. "Evolution Methods of Formation of Neuronet Models of Complex Economic Systems," Business Inform, RESEARCH CENTRE FOR INDUSTRIAL DEVELOPMENT PROBLEMS of NAS (KHARKIV, UKRAINE), Kharkiv National University of Economics, issue 1, pages 69-73.
  • Handle: RePEc:idp:bizinf:y:2014:i:1:p:69_73
    as

    Download full text from publisher

    File URL: https://www.business-inform.net/pdf/2014/1_0/69_73.pdf
    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:idp:bizinf:y:2014:i:1:p:69_73. 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: Khaustova Viktoriia (email available below). General contact details of provider: https://www.business-inform.net .

    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.