淡江大學機構典藏:Item 987654321/120394
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 62819/95882 (66%)
造访人次 : 4005463      在线人数 : 497
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/120394


    题名: Empirical Spatial Density based Emergency Medical Service Demand Forecast for Ambulance Allocation
    作者: Yihjia Tsai;Hwei Jen Lin;Pei-Wen Chi;Kelvin W. Lee
    关键词: multi-objective programming;Emergency Medical Service;Qradtree Decomposition;Particle Swarm Optimization;ambulance allocation
    日期: 2021-02-05
    上传时间: 2021-03-24 12:10:47 (UTC+8)
    出版者: World Scientific Publishing Co. Pte. Ltd.
    摘要: In a previous study, we solved the two-fold dynamic ambulance allocation problem, including forecasting the distribution of Emergency Medical Service (EMS) requesters and dynamically allocating ambulances according to the predicted distribution of requesters. In the definition of the coverage region, the Euclidean distance was used, which is not suitable for measuring the length of a route between two places. This study improved on the previous one by redefining the coverage region for practical application and providing a simulation model to verify the effectiveness of the proposed ambulance allocation method. The simulation results show the proposed allocation method provides higher demand coverage rates and shorter response distances than the official allocation.
    關聯: Advances in Data Science and Adaptive Analysis 13(1), 2150003
    DOI: 10.1142/S2424922X21500030
    显示于类别:[資訊工程學系暨研究所] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    index.html0KbHTML89检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈