AI for Climate Change Mitigation and Adaptation

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bhram dev

Abstract

Climate change poses one of the most significant challenges of our time, with far-reaching consequences for the environment, society, and the global economy. To address this urgent issue, the integration of artificial intelligence (AI) has emerged as a promising approach. This paper explores the role of AI in climate change mitigation and adaptation strategies. It provides an overview of the key AI techniques, such as machine learning, data analytics, and predictive modeling, that can be employed to combat climate change. The paper highlights the potential of AI in optimizing energy consumption, reducing greenhouse gas emissions, and enhancing climate resilience.

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How to Cite
AI for Climate Change Mitigation and Adaptation. (2019). Research-Gate Journal, 5(5). https://research-gate.in/index.php/Rgj/article/view/7
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Articles

How to Cite

AI for Climate Change Mitigation and Adaptation. (2019). Research-Gate Journal, 5(5). https://research-gate.in/index.php/Rgj/article/view/7

References

Hart, P. E. (1992). "Artificial Intelligence as Structural Estimation: Economic Interpretations of Deep Blue, Bonanza, and Alpha-Beta." AI Magazine, 13(3), 17-19.

Biermann, F., & Boas, I. (2010). "Preparing for a Warmer World: Towards a Global Governance System to Protect Climate Refugees." Global Environmental Politics, 10(1), 60-88.

Vapnik, V. N. (1995). "The Nature of Statistical Learning Theory." Springer.

Pachauri, R. K., & Reisinger, A. (2007). "Climate Change 2007: Synthesis Report." Contribution of Working Groups I, II, and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC.

Geman, S., & Geman, D. (1984). "Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images." IEEE Transactions on Pattern Analysis and Machine Intelligence, (6), 721-741.