城市洪涝应急物资需求预测

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关键词：城市洪涝灾害；案例推理；应急物资分配；需求预测；灾后恢复中图分类号：X43 文献标志码：ADOI：10.13800/j. cnki. xakjdxxb.2025.0501文章编号：1672-9315（2025）05-0845-10

Emergency material demand forecasting for urban floods

LUO Zhenmin1，2，3， SHEN Jiatong1，PAN Jingchao'，SU Bin1 ， LIU Litao1

（1.CollegeofSafetyScienceandEngineering，Xi’an UniversityofScienceand Technology，Xi’an7Oo54，China; 2.Shannxi Enginering Research Center for Industrial Process Safetyand EmergencyRescue，Xi’an71Oo54，China; 3.ShanxiKeyLaboratoryofPreventionandControlofoalFire，XinUiversityofienceandechologyXinina）

Abstract： In order to mitigate flood disaster impacts，optimize emergency material allocation mechanisms，and ensure scientific post-disaster material distribution，supply for disaster-stricken areas‘ needs，as well as the affected people’s basic livelihood and reconstruction.A case-based reasoning （CBR）model is developed for forecasting emergency material needs in urban flood scenarios.The model is validated using the July 20，2O21 extreme rainfall event in Zhengzhou as a representative case.The results indicate that the model achieves a relative error of 1.44% in predicting the number of people requiring emergency evacuation and resettlement，demonstrating high accuracy and practical applicability.The geographic characteristics and historical disaster data are identified as key influencing factors.

By retrieving and adapting similar past cases，the model effectively leverages historical experience to enhance decision-making under uncertainty，thereby improving the eficiency and precision of emergency response; Furthermore，the proposed framework offers operational feasibility and exhibits potential for extension to other natural disaster types，such as earthquakes and typhoons. Compared with traditional methods，the case-based reasoning approach provides better adaptability to the uncertainty of material demand in emergencies and offrs a strong support for the scientific alocation of resources and improved disaster recovery efforts.

Key Words： urban flood disaster; case-based reasoning; emergency supply distribution; demand prediction; disaster recovery

0 引言

受季风气候和复杂地形影响，中国暴雨洪水集中、洪涝灾害严重[1]。（剩余16077字）