AI-Driven Climate Modeling: Enhancing Predictions for Sustainable Development
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Abstract
Climate change poses unprecedented challenges, necessitating advanced modeling techniques for accurate predictions. This paper explores the application of AI in climate modeling, focusing on neural networks, reinforcement learning, and hybrid AI models. It evaluates the performance of AI-driven models in predicting extreme weather events, analyzing carbon emissions, and simulating long-term climate scenarios. The study underscores the potential of AI to enhance decision-making for sustainable development while addressing limitations in data availability and computational complexity.
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