Abstract
Climate change predictions have become crucial for understanding the impact of global warming and the development of effective mitigation strategies. Neural networks, a powerful tool in machine learning, have demonstrated significant potential in enhancing climate change predictions. This article explores the role of neural networks in climate change modeling, focusing on their ability to analyze complex datasets, predict environmental trends, and improve forecasting accuracy. It also discusses the opportunities offered by neural networks for better climate predictions and the challenges involved in integrating AI-driven models into climate science.
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