基于gis的多标准决策支持系统和医院选址的机器学习:案例研究奥兰,阿尔及利亚

Khadidja Benmoussa, D. Hamdadou, Zine El Abidine Roukh
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引用次数: 1

摘要

医院地点的选择是决策者为抵御大流行而必须做出的最重要的选择之一。这一决定可能在效率、预算等方面对疫情传播产生重大影响。本研究的主要目标是在奥兰阿尔格的维拉亚找到建立医院的理想地点。为此,我们采用地理信息系统与多准则分析法AHP相结合的方法,对生理定位、环境和经济等多种准则进行评价。本研究的另一个目的是评估自动学习的先进技术。随机森林(RF)法在奥兰村的医院选址模式。我们的研究结果可能有助于决策者了解这些站点的适用性,因为它提供了高度的信心,从而加快了控制covid - 19大流行的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GIS-Based Multi-Criteria Decision-Support System and Machine Learning for Hospital Site Selection: Case Study Oran, Algeria
The selection of hospital sites is one of the most important choice a decision maker has to take so as to resist the pandemic. The decision may considerably affect the outbreak transmission in terms of efficiency , budget, etc. The main targeted objective of this study is to find the ideal location where to set up a hospital in the willaya of Oran Alg. For this reason, we have used a geographic information system coupled to the multi-criteria analysis method AHP in order to evaluate diverse criteria of physiological positioning , environmental and economical. Another objective of this study is to evaluate the advanced techniques of the automatic learning . the method of the random forest (RF) for the patterning of the hospital site selection in the willaya of Oran. The result of our study may be useful to decision makers to know the suitability of the sites as it provides a high level of confidence and consequently accelerate the power to control the COVID19 pandemic.
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