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Medical Emergency Resource Allocation Model in Large-Scale Emergencies Based on Artificial Intelligence: Algorithm Development

机译:基于人工智能的大型紧急情况下的医疗应急资源分配模型:算法开发

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摘要

Background Before major emergencies occur, the government needs to prepare various emergency supplies in advance. To do this, it should consider the coordinated storage of different types of materials while ensuring that emergency materials are not missed or superfluous. Objective This paper aims to improve the dispatch and transportation efficiency of emergency materials under a model in which the government makes full use of Internet of Things technology and artificial intelligence technology. Methods The paper established a model for emergency material preparation and dispatch based on queueing theory and further established a workflow system for emergency material preparation, dispatch, and transportation based on a Petri net, resulting in a highly efficient emergency material preparation and dispatch simulation system framework. Results A decision support platform was designed to integrate all the algorithms and principles proposed. Conclusions The resulting framework can effectively coordinate the workflow of emergency material preparation and dispatch, helping to shorten the total time of emergency material preparation, dispatch, and transportation.
机译:背景技术在主要紧急情况发生之前,政府需要提前准备各种应急供应。为此,它应该考虑不同类型材料的协调存储,同时确保不遗漏或多余的应急材料。目的本文旨在提高政府充分利用技术和人工智能技术互联网的模型下应急材料的调度和运输效率。方法采用基于排队理论的应急材料准备和发货模型,进一步建立了基于Petri网的应急材料准备,调度和运输工作流程系统,导致高效的应急材料准备和调度仿真系统框架。结果决策支持平台旨在集成所有算法和原则。结论所产生的框架可以有效地协调应急材料准备和派遣的工作流程,有助于缩短应急材料准备,派遣和运输的总时间。

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