Neural modeling classification of western and transition European economies based on energy patterns

摘要

This paper aims in comparing countries with different energy strategies and also in demonstrating the close connection between environment and financial development in the ex-eastern European economies, during their transition to market ones. Multi-layer perceptrons (MLPs) and radial-basis function (RBF) neural networks have been developed which are trained to classify countries based on their emissions of carbon, sulphur and nitrogen oxides, and on their Gross National Income. Three typical ex-eastern economies (Russia, Poland and Hungary) and three main western economies (United States, France and United Kingdom) were studied in this research effort. Results showed that the linkage between environmental pollution and economic growth has been maintained in the ex-eastern countries.