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Journal of Biosensors & Renewable sources

Mini ReviewOpen Access

Artificial Neural Networks Based Modeling in Sustainable Energy Domain Volume 1 - Issue 1

Sorin Ciortan*

  • Dunarea de Jos University of Galati, Romania

Received: December 17, 2019   Published: December 17, 2019

Corresponding author: Sorin Ciortan, “Dunarea de Jos” University of Galati, Romania

DOI: 10.32474/JBRS.2019.01.000105


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The economic and technical development of human society in late years put a heavy pressure on the natural resources of our planet. The increasing need for both material and energy resources lead not just to an extensive consumption of existing ones but also to an increase of pollution, with negative and irreversible consequences on every living being on Earth. One of the most destructive is the constant rise of the atmosphere temperature as consequence of so called “greenhouse effect”: the accumulation of some gases among the most important is CO2, produced mainly by classical energy sources Figure 1, acting as a shield and maintaining the heat generated by solar radiation. This fact induces a “domino” effect on whole planet, starting with the glacier’s melting (since 1973 the glaciers’ melting ratio it has grown with 77% [3]) and ending with random climate changing at planetary scale.

Introduction| Sustainable Energy Sources - Modeling and Prediction| Neural Networks’-Based Modeling| Conclusion| References|