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Urban Disaster Risk Assessment and Decision-making Model Based on Big Data and AI

In: Proceedings of the 2025 3rd International Conference on Digital Economy and Management Science (CDEMS 2025)

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  • Jinglin Wu

    (China University of Geosciences, School of Economics and Management)

Abstract

With the rapid development of urbanization, cities are facing various disaster risks. Traditional disaster risk assessment and decision-making methods have limitations in dealing with complex and dynamic urban environments. This paper focuses on the construction of an urban disaster risk assessment and decision-making model by integrating big data and artificial intelligence (AI) technologies. By collecting and analyzing a large amount of multi-source data related to urban disasters, such as geographical information, meteorological data, social and economic data, and historical disaster data, we can obtain a more comprehensive and accurate understanding of disaster risks. Advanced AI algorithms, including machine learning and deep learning, are employed to process and analyze these data to identify patterns, trends, and potential risk factors. The model not only provides accurate risk assessment results but also generates intelligent decision-making suggestions for disaster prevention, mitigation, and response. It can help urban managers and relevant departments make more scientific and timely decisions to reduce the losses caused by disasters. This research is of great significance for improving urban disaster resilience and ensuring the safety and sustainable development of cities.

Suggested Citation

  • Jinglin Wu, 2025. "Urban Disaster Risk Assessment and Decision-making Model Based on Big Data and AI," Advances in Economics, Business and Management Research, in: Wenke Zang & Chunping Xia (ed.), Proceedings of the 2025 3rd International Conference on Digital Economy and Management Science (CDEMS 2025), pages 587-594, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-770-0_66
    DOI: 10.2991/978-94-6463-770-0_66
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