Abstract
Natural disasters have been an enduring and formidable challenge throughout human history, causing widespread devastation to communities and ecosystems. The significance of predicting these events lies in the ability to mitigate their impact on human lives, infrastructure, and the environment. Timely and accurate prediction empowers communities to take proactive measures, enabling better preparedness, response, and recovery. In the absence of such forecasting capabilities, the toll of natural disasters can be catastrophic, leading to loss of life, displacement of populations, and economic setbacks. Therefore, the development of predictive models, such as artificial neural networks (ANNs) and other data-driven approaches, is pivotal in addressing the escalating threats posed by natural disasters.
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