The Role of AI in Mitigating Climate Change: Predictive Modelling for Renewable Energy Deployment

3Citations
Citations of this article
13Readers
Mendeley users who have this article in their library.

Abstract

This study looks at how AI algorithms like Random Forest, Support Vector Machines (SVM), and Deep Boltzmann Machine (DBM) can be used for predictive modeling to make it easier to use renewable energy sources while reducing the negative effects of climate change. Predictive models based on Artificial Intelligence show possible ways to get the most out of green energy sources, which could lead to fewer carbon emissions. The results of the preliminary studies show that these AI systems can make accurate predictions about how green energy will be made because they are good at making predictions and generalizing. This feature makes it possible to use resources effectively, which improves the reliability of the grid and encourages more people to use green energy sources. Ultimately, employing these AI programs will serve as powerful tools in combating climate change and fostering a more sustainable and eco-friendly environment.

Cite

CITATION STYLE

APA

Alharbe, N., & Alluhaibi, R. (2023). The Role of AI in Mitigating Climate Change: Predictive Modelling for Renewable Energy Deployment. International Journal of Advanced Computer Science and Applications, 14(12), 114–121. https://doi.org/10.14569/IJACSA.2023.0141211

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free