Diversification of energy supplies is one of the main priorities of the energy policy of the developed countries. The major objective of this research is the model for predicting the economic impact of renewable energy using artificial intelligence techniques. This has been achieved by using the neural networks for the various issues related to renewable energy. The designed model consist in identification of those macroeconomic indicators that are required for the database creation, validation and testing in the view of obtaining the smallest error in the validation set for predicting the renewable energy impact upon the economy. The performance of the model was also revealed by comparing control graphs.
CITATION STYLE
Chirita, M., Sarpe, D. A., Cristache, N., Micu, A., & Capatina, A. (2017). PREDICTING THE ECONOMIC IMPACT OF USING RENEWABLE ENERGY BY MODELLING THROUGH ARTIFICIAL INTELLIGENCE TECHNIQUES. European Journal of Sustainable Development, 6(1). https://doi.org/10.14207/ejsd.2017.v6n1p42
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