Abstract
Artificial intelligence (AI) and neural networks have shown immense potential in improving disaster risk assessment by providing more accurate and efficient models for predicting, analyzing, and mitigating the impacts of natural and man-made disasters. These technologies can analyze complex data from various sources, such as satellite imagery, historical data, and social media, to assess vulnerability, monitor hazard events, and forecast disaster impacts. This article explores the role of AI and neural networks in disaster risk assessment, highlighting their applications in hazard prediction, damage assessment, and emergency response. We also discuss the challenges, opportunities, and future trends in integrating AI into disaster risk management frameworks.
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