城市疫情态势发展与动态调控可视分析

王松; 陈仕杰; 李杭霖; 李孝慧; 冯琼芳; 王慧杰

doi:10.11959/j.issn.2096-0271.2023027

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城市疫情态势发展与动态调控可视分析

研究 | 更新时间：2024-06-03

- 城市疫情态势发展与动态调控可视分析
- Visual analytics of urban epidemic situation development and dynamic regulation
- 大数据 2023年9卷第6期页码：110-123
- 作者机构：
  
  1. 西南科技大学计算机科学与技术学院，四川绵阳 621010
  2. 电子科技大学计算机科学与工程学院，四川成都 611731
  3. 西南交通大学计算机与人工智能学院，四川成都 611756
- 作者简介：
  
  [ "王松（1989- ），男，博士，西南科技大学计算机科学与技术学院讲师，主要研究方向为可视化与可视分析、智能交互、混合现实。" ]
  [ "陈仕杰（1998- ），男，西南科技大学计算机科学与技术学院硕士生，主要研究方向为可视化与可视分析。" ]
  [ "李杭霖（2000- ），女，电子科技大学计算机科学与工程学院硕士生，主要研究方向为可视化与可视分析。" ]
  [ "李孝慧（1998- ），女，西南交通大学计算机与人工智能学院硕士生，主要研究方向为可视化与可视分析。" ]
  [ "冯琼芳（2001- ），女，西南科技大学计算机科学与技术学院在读，主要研究为可视化与可视分析。" ]
  [ "王慧杰（2000- ），男，西南科技大学计算机科学与技术学院在读，主要研究为可视化与可视分析。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61872304);四川省自然科学基金资助项目;Sichuan Natural Science Foundation of China(2022NSFSC0961);西南科技大学博士点基金资助项目;Southwest University of Science and Technology PhD Fund Grant(19ZX7144);西南科技大学一般教育教学改革与研究项目;Southwest University of Science and Technology General Education Reform Fund Grant(22xn0048)
- DOI：10.11959/j.issn.2096-0271.2023027
  中图分类号： TP391
- 网络首发：2023-11，
  
  纸质出版：2023-11-15
- 稿件说明：
移动端阅览
王松, 陈仕杰, 李杭霖, 等. 城市疫情态势发展与动态调控可视分析[J]. 大数据, 2023,9(6):110-123.

Song WANG, Shijie CHEN, Hanglin LI, et al. Visual analytics of urban epidemic situation development and dynamic regulation[J]. Big data research, 2023, 9(6): 110-123.
王松, 陈仕杰, 李杭霖, 等. 城市疫情态势发展与动态调控可视分析[J]. 大数据, 2023,9(6):110-123. DOI： 10.11959/j.issn.2096-0271.2023027.

Song WANG, Shijie CHEN, Hanglin LI, et al. Visual analytics of urban epidemic situation development and dynamic regulation[J]. Big data research, 2023, 9(6): 110-123. DOI： 10.11959/j.issn.2096-0271.2023027.

摘要

为了解决新冠肺炎疫情医疗资源的合理调配问题，以武汉方舱新冠肺炎疫情数据为基础，融合舆情、时空轨迹等多源数据，针对疫情防控搭建了方舱医院动态调控平台。引入水滴图表征方式动态监测方舱医院，采用主题模型融合情感词典提取群众情感特征，并借助WordStream呈现城市舆情发展，提出基于医院负载量的路径规划算法实现合理路线推荐，提供面向群众的科普信息和城市复苏板块以提升抗疫信心。该系统有利于实现人力、物力的合理配置，及时引导群众的情绪动向，关注新政策/决定发布后的舆情变化，减缓患者聚集现象。最后，结合多组案例分析验证了系统的功能性和有效性。

Abstract

In order to solve the reasonable allocation of limited medical resources for patients

a visual platform for dynamic control of cabin hospital was built based on the dataset of the COVID-19 epidemic in Wuhan cabin hospital

which integrates multi-source data such as public opinion

space-time trajectory and science popularization.The droppingwater diagram was introduced to dynamically monitor the overall situation of the cabin hospital.The theme model and sentiment dictionary were used to extract the emotional features of the masses

the WordStream were used to visually present the trend of urban public opinion.The path planning algorithm based on hospital load capacity were built for treatment route

the population-oriented science information of access to cabin hospital and the urban recovery model can enhance anti-epidemic confidence.The system is helpful to realize the reasonable allocation of human and material resources

timely guide the emotional trend of the masses

pay attention to the change of public opinion after the release of new polices/decisions

and slow down the phenomenon of patients gathering.The function and effectiveness of the system was verified by the analysis of several cases.

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references

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