基于空间聚类的北京H1N1流感仿真分析

doi:10.16182/j.issn1004731x.joss.201709032

系统仿真学报 ›› 2017, Vol. 29 ›› Issue (9): 2115-2121.doi: 10.16182/j.issn1004731x.joss.201709032

基于空间聚类的北京H1N1流感仿真分析

赵翌僮¹, 梅珊¹, 马亮¹, 张伟²

1.国防科技大学信息系统与管理学院,湖南长沙 410073;
2.中国空间技术研究院通信卫星事业部,北京 100101

收稿日期:2017-06-15 发布日期:2020-06-02
作者简介:赵翌僮(1993-),男,北京,硕士生,研究方向为体系工程与体系仿真;梅珊(1981-),女,湖南长沙,博士,副教授,研究方向为基于Agent和复杂网络的传染病仿真。
基金资助:
国家自然科学基金(71373282)

Simulation Analysis of Beijing H1N1 Influenza Based on Spatial Clustering

Zhao Yitong¹, Mei Shan¹, Ma Liang¹, Zhang Wei²

1. College of Information System and Management, National University of Defense Technology, Changsha 410073, China;
2. Institute of Telecommunication Satellite, China Academy of Space Technology, Beijing 110101, China

Received:2017-06-15 Published:2020-06-02

摘要/Abstract

摘要： 空间聚类广泛用于传染病的监测、预防和控制。传染病与普通疾病在早期具有相似的症状,使得传染病数据处理和分析更为困难。采用基于Agent的仿真建模方法,生成北京暴发H1N1流感的仿真数据。基于4组分布形状与规模不同的数据,对2种空间聚类算法的疫情监测结果进行分析。结果表明,通过空间聚类算法对Agent仿真数据进行分析,有助于揭示疫情的扩散规律,进而在传染病监测和防控方面起到积极作用。

关键词: 基于Agent建模与仿真, 传染病监测, 空间聚类, 空间扫描统计

Abstract: Spatial cluster detection is widely used for disease surveillance, prevention and containment. In the early stages of illness, epidemics have similar symptoms to common diseases, making infectious disease data processing and analysis difficult. The Agent based modeling and simulation was used to generate H1N1 influenza data in Beijing. By designing a set of experiments, the epidemic monitoring results of two spatial clustering algorithms were analyzed. The results show that, using spatial clustering algorithms to analyze the simulation data of the epidemics can help to reveal the spread of the epidemic and play a positive role in the surveillance and prevention of infectious diseases.

Key words: agent-based modeling and simulation, disease surveillance, spatial clustering, statistics and analysis

中图分类号:

赵翌僮, 梅珊, 马亮, 张伟. 基于空间聚类的北京H1N1流感仿真分析[J]. 系统仿真学报, 2017, 29(9): 2115-2121.

Zhao Yitong, Mei Shan, Ma Liang, Zhang Wei. Simulation Analysis of Beijing H1N1 Influenza Based on Spatial Clustering[J]. Journal of System Simulation, 2017, 29(9): 2115-2121.

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基于空间聚类的北京H1N1流感仿真分析

Simulation Analysis of Beijing H1N1 Influenza Based on Spatial Clustering

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