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考虑自然灾害等多因素的BWM-GIS城市医院选址
引用本文:刘倩,高轩能. 考虑自然灾害等多因素的BWM-GIS城市医院选址[J]. 华侨大学学报(自然科学版), 2022, 43(3): 330-337. DOI: 10.11830/ISSN.1000-5013.202108030
作者姓名:刘倩  高轩能
作者单位:华侨大学 土木工程学院, 福建 厦门 361021
基金项目:国家自然科学基金资助项目(51278208);;福建省科技计划重点项目(2018Y0063);
摘    要:为实现城市医疗资源合理配置,对城市现有医院位置进行科学性评估和对新建医院优化性选址.首先,应用ArcGIS软件构建泰森多边形,对现有医院的分布进行合理性评判,并考虑安全性、可达性和经济性等影响因素构建医院选址评价体系.其次,应用最优-最劣法(BWM)计算指标权重,并将其输入Spatial Analyst叠置分析中,根据加权线性组合(WLC)得到适宜新建医院的选址备选点.最后,采用BP神经网络算法对备选点进行比较,得出最优新建医院选址位置.研究结果表明:考虑自然灾害等多因素的医院选址模型优于仅以可达性为目标的选址模型,同时,也验证了该模型和算法在城市医院选址定量分析中的适用性和准确性.

关 键 词:城市医院  选址  自然灾害  适宜度  最优-最劣法  地理信息系统  BP神经网络

Urban Hospital Site Selection Using BWM-GIS Considering Natural Disasters and Other Factors
LIU Qian,GAO Xuanneng. Urban Hospital Site Selection Using BWM-GIS Considering Natural Disasters and Other Factors[J]. Journal of Huaqiao University(Natural Science), 2022, 43(3): 330-337. DOI: 10.11830/ISSN.1000-5013.202108030
Authors:LIU Qian  GAO Xuanneng
Affiliation:College of Civil Engineering, Huaqiao University, Xiamen 361021, China
Abstract:In order to rationally allocate urban medical resources, the location of existing urban hospitals is scientifically evaluated, and newly-built hospital site selection is optimized. Tyson polygon with ArcGIS software is constructed, the rationality of the distribution of existing hospitals is evaluated, and the hospital site selection evaluation system is established considering the influencing factors such as safety, accessibility and economy. The best-worst method(BWM)is used to calculate the index weights,which are put into Spatial Analyst overlay analysis. According to the weighted linear combination(WLC), the suitable candidate sites for newly-built hospitals site selection are obtained. The the candidate sites are compared by BP neural network algorithm, and the optimal location of newly-built hospital is obtained. The result shows that, the hospital site selection model considering natural disasters and other factors disasters is better than the location model only considering accessibility. The applicability and accuracy of the model and algorithm on the quantitative analysis of urban hospital site selection are verified.
Keywords:urban hospital  site selection  natural disaster  suitability  best-worst method  geographic information system  BP neural network
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