Abstract
The repercussions of progressive environmental deterioration in the world have generated studies such as the one presented through the Kuznet environmental curve, which theorizes phenomena that relate the use of natural resources with the increase in the Gross Domestic Product (GDP) of economies. Thus, the case analyzed in this chapter makes it possible to identify the effect of the growth of carbon emissions as a function of per capita GDP in American and European countries, its behavior and the results generated by it. The above responds to the provisions of Sustainable Development Goals 8 “Decent Work and Economic Growth” and 13 “Climate Action”, which correspond to economic growth and climate action, respectively. The methodological development of this study is based on the construction of a deep neural network, which allows concluding on the results of the economies of America and Europe and identifying those that have implemented environmentally friendly processes and, at the same time, sustainable economic growth.
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Quintero, A., Gaitán-Angulo, M., Gómez-Caicedo, M.I., Suárez, Á.L.M., Gil, R.E.R. (2022). Effect of the Growth of Carbon Emissions as a Function of GDP Per Capita and Its Relationship with the SDG in American and European Countries: An Application of Neural Networks. In: Verdegay, J.L., Brito, J., Cruz, C. (eds) Computational Intelligence Methodologies Applied to Sustainable Development Goals. Studies in Computational Intelligence, vol 1036. Springer, Cham. https://doi.org/10.1007/978-3-030-97344-5_13
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