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Predicting the Economic Impact of Using Renewable Energy by Modelling Through Artificial Intelligence Techniques
European Journal of Sustainable Development
View Archive Info| Field | Value | |
| Title |
Predicting the Economic Impact of Using Renewable Energy by Modelling Through Artificial Intelligence Techniques
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| Creator |
Chirita, Mioara
Sarpe, Daniela Ancuta Cristache, Nicoleta Micu, Adrian Capatina, Alexandru |
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| Description |
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. Key words: renewable energy, economic growth, forecast, macroeconomic indicators
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| Publisher |
European Center of Sustainable Development
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| Contributor |
—
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| Date |
2017-01-31
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| Type |
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion — |
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| Format |
application/pdf
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| Identifier |
http://www.ecsdev.org/ojs/index.php/ejsd/article/view/437
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| Source |
European Journal of Sustainable Development; Vol 6, No 1; 42-56
2239-6101 2239-5938 |
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| Language |
eng
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| Relation |
http://www.ecsdev.org/ojs/index.php/ejsd/article/view/437/434
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| Rights |
This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License.Authors of articles published in the European Journal of Sustainable Development retain copyright on their articles. Authors are therefore free to disseminate and re-publish their articles, subject to any requirements of third-party copyright owners and subject to the original publication being fully cited. The ability to copy, download, forward or otherwise distribute any materials is always subject to any copyright notices displayed. Copyright notices must be displayed prominently and may not be obliterated, deleted or hidden, totally or partially.
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