A machine learning approach for predicting the relationship between energy resources and economic development

The linkage between energy resources and economic development is a topic of great interest. Research in this area is also motivated by contemporary concerns about global climate change, carbon emissions fluctuating crude oil prices, and the security of energy supply. The purpose of this research is...

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Bibliographic Details
Published in:Physica A 2018-04, Vol.495, p.211-214
Main Authors: Cogoljević, Dušan, Alizamir, Meysam, Piljan, Ivan, Piljan, Tatjana, Prljić, Katarina, Zimonjić, Stefan
Format: Article
Language:English
Subjects:
Economic development
Energy usage
Prediction
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Summary:The linkage between energy resources and economic development is a topic of great interest. Research in this area is also motivated by contemporary concerns about global climate change, carbon emissions fluctuating crude oil prices, and the security of energy supply. The purpose of this research is to develop and apply the machine learning approach to predict gross domestic product (GDP) based on the mix of energy resources. Our results indicate that GDP predictive accuracy can be improved slightly by applying a machine learning approach. •In this investigation was analyzed the economic development prediction.•Machine learning approach to predict economic development.•Machine learning approach can be utilized in applications of economic development forecasting.
ISSN:0378-4371
1873-2119
DOI:10.1016/j.physa.2017.12.082