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

DOI

10.2991/978-94-6463-770-0_66How to use a DOI?

Keywords

Big Data; AI; Urban Disasters; Risk Assessment; Decision-making Model

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.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Jinglin Wu
PY  - 2025
DA  - 2025/06/26
TI  - Urban Disaster Risk Assessment and Decision-making Model Based on Big Data and AI
BT  - Proceedings of the 2025 3rd International Conference on Digital Economy and Management Science (CDEMS 2025)
PB  - Atlantis Press
SP  - 587
EP  - 594
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-770-0_66
DO  - 10.2991/978-94-6463-770-0_66
ID  - Wu2025
ER  -