Neural Network Principles To Classify Economic Data
The increased globalization makes every country more and more responsible for its actions that are meant to support the price stability and the fiscal position sustainability in an unpredictable world. Decisions makers can provide the right solutions to overcome the latest global economic crisis by using methods of classifying the continuously growing amounts of digital economic data. The principles of neural networks are applied in order to classify a set of countries according to their statistical data for economic indicators provided by the European Committee. The results and performance of this classification technique is discussed in the final section of the paper.
Volume (Year): 63.4-5 (2012)
Issue (Month): 4-5 ()
|Contact details of provider:|| Postal: Lucian Blaga University of Sibiu, Faculty of Economic Sciences Dumbravii Avenue, No.17, postal code 550324, Sibiu, Romania|
Phone: 004 0269 210375
Fax: 004 0269 210375
Web page: http://economice.ulbsibiu.ro/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:blg:reveco:v:63.4-5:y:2012:i:4-5:p:223-233. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Eduard Alexandru Stoica)
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.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.