Abstract
Natural disasters pose significant challenges to human safety, infrastructure, and economies. Accurate prediction and timely response are essential to minimize the impacts of these events. AI-enhanced learning algorithms, particularly machine learning and deep learning models, have demonstrated great potential in predicting natural disasters such as hurricanes, earthquakes, floods, and wildfires. This article explores the role of AI in improving disaster prediction, focusing on the use of advanced learning algorithms to analyze vast amounts of data and provide accurate forecasts. The article discusses various AI techniques, including neural networks, support vector machines, and ensemble methods, in the context of disaster prediction. It also addresses the challenges and opportunities in implementing AI-driven systems for real-time disaster forecasting
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