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首页> 外文期刊>Annals of Operations Research >Finding of urban rainstorm and waterlogging disasters based on microblogging data and the location-routing problem model of urban emergency logistics
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Finding of urban rainstorm and waterlogging disasters based on microblogging data and the location-routing problem model of urban emergency logistics

机译:基于微博数据的城市暴雨和涝灾,城市应急物流定位路由问题模型

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摘要

Due to the climate change and the rapid progress of urbanization, extreme weather disasters such as urban rainstorm and waterlogging are frequent. Therefore, how to find the waterlogging points in the presence of disasters and how to optimize the distribution of urban emergency logistics and reduce the negative impact of disasters have become a hot and difficult issue for government departments and scholars. First of all, the idea and method of using the big data of microblogging to obtain urban rainstorm and waterlogging disasters and public sentiment are put forward. In addition,this thesis constructed the location-routing problem model of urban emergency logistics in the situation of rainstorm and waterlogging disaster, and found out the dynamic emergency distribution path of Nanjing in the situation of waterlogging disaster by using NSGA-III algorithm. Research shows that the risk management of urban rainstorm and waterlogging disasters, together with social media data, is a feasible way to obtain on-site data of disasters and carry out risk assessment of disasters. At the same time, the emergency logistics location-positioning model and algorithm can provide a reference for similar disaster emergency logistics distribution network and the conclusion can provide empirical reference for cities to cope with rainstorm and waterlogging disasters.
机译:由于气候变化和城市化的快速进步,城市暴雨和涝渍等极端天气灾害频繁。因此,如何在存在灾害和如何优化城市应急物流的分布并降低灾害的负面影响成为政府部门和学者的负面影响。首先,提出了使用微博的大数据来获得城市暴雨和涝灾和公共情绪的理念和方法。此外,本文在暴雨和涝灾情况下构建了城市应急物流的位置路由问题模型,并用NSGA-III算法发现了南京南京动态应急分布路径。研究表明,城市暴雨和涝灾的风险管理以及社交媒体数据,是获得灾害现场数据的可行方法,并对灾害进行风险评估。同时,应急物流定位模型和算法可以为类似的灾害应急物流配送网络提供参考,结论可以为城市应对暴雨和涝灾的效率提供实证参考。

著录项

  • 来源
    《Annals of Operations Research》 |2020年第2期|865-896|共32页
  • 作者单位

    Shanghai Maritime Univ Sch Econ & Management Shanghai Peoples R China|Nanjing Univ Informat Sci & Technol Sch Econ & Management Nanjing Peoples R China|Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Climate & Meteorol Disaste Nanjing Peoples R China;

    Nanjing Univ Informat Sci & Technol Sch Econ & Management Nanjing Peoples R China;

    Nanjing Univ Informat Sci & Technol Sch Econ & Management Nanjing Peoples R China;

    Shanghai Maritime Univ Sch Econ & Management Shanghai Peoples R China|Nanjing Univ Informat Sci & Technol Sch Econ & Management Nanjing Peoples R China|Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Climate & Meteorol Disaste Nanjing Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Microblogging data; Urban rainstorm and waterlogging disasters; Location-routing problem; NSGA-III algorithm;

    机译:微博数据;城市暴雨和涝灾;位置路由问题;NSGA-III算法;

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