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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/120394

    Title: Empirical Spatial Density based Emergency Medical Service Demand Forecast for Ambulance Allocation
    Authors: Yihjia Tsai;Hwei Jen Lin;Pei-Wen Chi;Kelvin W. Lee
    Keywords: multi-objective programming;Emergency Medical Service;Qradtree Decomposition;Particle Swarm Optimization;ambulance allocation
    Date: 2021-02-05
    Issue Date: 2021-03-24 12:10:47 (UTC+8)
    Publisher: World Scientific Publishing Co. Pte. Ltd.
    Abstract: 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.
    Relation: Advances in Data Science and Adaptive Analysis 13(1), 2150003
    DOI: 10.1142/S2424922X21500030
    Appears in Collections:[資訊工程學系暨研究所] 期刊論文

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