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Research Article | Open Access |

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

Author 1: Nawaf Alharbe Author 2: Reyadh Alluhaibi
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 14, No. 12 · Published 2023

DOI: https://doi.org/10.14569/IJACSA.2023.0141211

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.

Keywords

How to Cite this Article

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). https://doi.org/10.14569/IJACSA.2023.0141211

Alharbe, Nawaf, and Reyadh Alluhaibi. "The Role of AI in Mitigating Climate Change: Predictive Modelling for Renewable Energy Deployment." International Journal of Advanced Computer Science and Applications, vol. 14, no. 12, 2023, https://doi.org/10.14569/IJACSA.2023.0141211.

@article{Alharbe2023,
  title     = {The Role of AI in Mitigating Climate Change: Predictive Modelling for Renewable Energy Deployment},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {14},
  number    = {12},
  year      = {2023},
  publisher = {The Science and Information Organization},
  author    = {Nawaf Alharbe and Reyadh Alluhaibi},
  doi       = {10.14569/IJACSA.2023.0141211},
  url       = {https://doi.org/10.14569/IJACSA.2023.0141211}
}

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