Moldova Republic’s Gross Domestic Product Prevision Using artificial Neural Network Techniques
Considering the present economical status, it is necessary to efficiently manage the Gross Domestic Product (GDP) especially for developing countries. Thus, it will be advantageous to have some knowledge about future trends or specific values of the GDP in accordingly to the dynamics of certain economics indices such as Investment in fixed capital, Imports from other countries etc. The present paper contains the basic research to determine the possibility of using artificial intelligence for the prevision of future GDP. In order to determine the GDP of Moldova Republic the following data were considered: Imports from other countries, Investment in fixed capital, Retail trade and Industrial production. A feed forward artificial neural network (ANN), with 10 hidden neurons, was trained and tested. After 590 iterations a maximum training absolute error of 0.008983 was obtained. Also the absolute validation error was 0.012664 and the network error was 0.000248. The final testing errors belongs to the [0.00; 2.47] interval of absolute values and to the [0.00; 0.23] interval of relative values. The results offer the bases for the future researches.
Volume (Year): X (2010)
Issue (Month): 1 (May)
|Contact details of provider:|| Web page: http://www.univ-ovidius.ro/facultatea-de-stiinte-economice|
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:ovi:oviste:v:10:y:2010:i:1:p:667-671. 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: (Gheorghiu Gabriela)
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.