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Analyzing Economical Performance of Central-East-European Countries Using Neural Networks and Cluster Analysis

Adrian Costea, Antonina Kloptchenko, Barbro Back, Analyzing Economical Performance of Central-East-European Countries Using Neural Networks and Cluster Analysis. In: Proceedings of the Fifth International Symposium on Economic Informatics, Bucharest, Romania, May 10-13. , 1006-1011, 2001.

Abstract:

This paper presents two different approaches to analyze economical performances of countries with rapidly developing market economies. Firstly, data in form of economical performance variables were clustered using two different techniques: neural networks in form of self-organizing maps and statistical cluster analysis. Secondly, the results of these two methods were compared to decide what are the advantages and disadvantages of them when they are used to assist the investors assessing economical performance of countries.

BibTeX entry:

@INPROCEEDINGS{inpCoKlBa01a,
  title = {Analyzing Economical Performance of Central-East-European Countries Using Neural Networks and Cluster Analysis},
  booktitle = {Proceedings of the Fifth International Symposium on Economic Informatics, Bucharest, Romania, May 10-13. },
  author = {Costea, Adrian and Kloptchenko, Antonina and Back, Barbro},
  pages = {1006-1011},
  year = {2001},
}

Belongs to TUCS Research Unit(s): Data Mining and Knowledge Management Laboratory

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