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Self-Organizing Neural Networks for the Analysis of Country Development

Publication at Faculty of Mathematics and Physics |
2018

Abstract

National economies can be influenced in various ways. Our research is focused on post-Soviet and Spanish speaking countries.

To understand the actual state of the countries and to assess possible trends for their development, we use the SOM-networks. Based on development indicators provided by the World Bank, our approach is shown to explain both major trends as well as changes in the development of the countries.

Stable economies are characterized by minor changes and sustained development. Crises, on the other hand, tend to manifest themselves rather by turbulent movements of the economy.

This paper demonstrates various changes in the country's economy, such as economic and moral crises, or socio-political turmoils, but also positive events like joining economical unions or organizing international sports events. Further, we will provide possible reasons for the causes of these trends and crises.