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Employing a Radial-Basis Function Artificial Neural Network to Classify Western and Transition European Economies Based on the Emissions of Air Pollutants and on Their Income

Abstract : This paper aims in comparing countries with different energy strategies, and demonstrate the close connection between environment and economic growth in the ex-Eastern countries, during their transition to market economies. We have developed a radial-basis function neural network system, which is trained to classify countries based on their emissions of carbon, sulphur and nitrogen oxides, and on their Gross National Income. We used three countries representative of ex-Eastern economies (Russia, Poland and Hungary) and three countries representative of Western economies (United States, France and United Kingdom). Results showed that the linkage between environmental pollution and economic growth has been maintained in ex-Eastern countries.
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Kyriaki Kitikidou, Lazaros Iliadis. Employing a Radial-Basis Function Artificial Neural Network to Classify Western and Transition European Economies Based on the Emissions of Air Pollutants and on Their Income. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. pp.141-149, ⟨10.1007/978-3-642-23960-1_18⟩. ⟨hal-01571479⟩

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