摘 要:为评估各个地区的出行风险度,选取周边的风险百分比以及确诊人数等多种数据为影响因素,采用 Topsis 算法根据出行风险百分比对不同地区进行排序。疫情的爆发将疫苗接种推向高潮,为降低人流密度,减少人员交叉接触,对于不同的活动实施分流计划。结合活动人数、时间段以及活动类型等各项数据,运用 Topsis 算法对不同的活动进行排序,提高活动的效率,实现资源利用率最大化,从而促进各类活动的有序进行。
关键词:Topsis 算法;疫情;分流
DOI:10.19850/j.cnki.2096-4706.2021.18.005
基金项目:2021 年省级大学生创新创业训 练计划项目(S202112574009)
中图分类号:TP311 文献标识码:A 文章编号:2096-4706(2021)18-0017-04
Application Research on Epidemic Situation Monitoring System Based on Topsis Algorithm
ZHANG Xiaojie, LI Jing, DENG Ziyan, LIN Qiaoyi, WANG Xin
(Neusoft Institute Guangdong, Foshan 528225, China)
Abstract: In order to evaluate the travel risk degree of each region, a variety of data such as the surrounding risk percentage and the number of confirmed patients are selected as influencing factors, and Topsis algorithm is used to sort different regions according to the travel risk percentage. The outbreak of the epidemic pushed vaccination to a climax. In order to reduce the flow density and reduce personnel cross contact, split-flow plans are implemented for different activities. Combined with the data of the people number of activities, time period and type of activities, Topsis algorithm is used to sort different activities, improves the efficiency of activities and maximizes the utilization of resources, so as to promote the orderly progress of various activities.
Keywords: Topsis algorithm; epidemic situation; split-flow
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作者简介:张晓洁(2000.09—),女,汉族,广东潮州人,本科在读,研究方向:软件工程;通讯作者:李晶(1987.01—),女, 汉族,陕西商洛人,副教授,硕士,研究方向:软件开发,虚拟现实。