NEURAL NETWORK PRINCIPLES TO CLASSIFY ECONOMIC DATA

STEFAN Raluca-Mariana, Academy of Economic Studies

SERBAN Mariuta, University of Pitesti

Abstract:
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.

Keywords: neural networks, supervised learning, data classification, economic prosperity

JEL Classification: A12, C15, C38, C45, C52, C53, C63, C88

Volume: 63.4-5, Issue: 4-5

Pages: 223 - 233

Publication date: , 2012

Download the article: http://economice.ulbsibiu.ro/revista.economica/archive/RE%204-5-63-2012.pdf

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