Renewable Energy Sources are on Track for Climate Change Mitigation: Classification of their Carbon Intensity by Neural Approach

Rim JEMLI¹, Nouri Chtourou²

High School of Commerce of Sfax,Tunisia

Abstract

During the last decades, alerts raised warning from a more and more severe climate change. In this field, country's energy policy is a main question for tackling climate change. In fact, the man is commonly condemned by the climate change intensification. This can be closely linked to his overuse of fossil fuels. Those are the biggest issuers of greenhouse gases, particularly dioxide of carbon. Hence, for reducing carbon emissions the alternative is for renewable energy. This paper aims to highlight the environmental value of renewable energy in matter of carbon emissions dejection. In that regard, the neural approach was applied to approve the weak carbon intensity of renewable energy. Our results amply support the literary thoughts about renewable energy effectiveness and its low carbon emissions. So, renewable sources are on track for climate change mitigation.

Keywords

• Renewable Energy, Climate Change, Neural Networks

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Cite this Article as Follows

Rim JEMLI, Nouri Chtourou. Renewable Energy Sources are on Track for Climate Change Mitigation: Classification of their Carbon Intensity by Neural Approach. International Conference on Human Machine Interaction 2014. Vol. 1. Chennai: Association of Scientists, Developers and Faculties, 2014. 70-75. Print.