中文版 | English
题名

基于轨迹数据精准防疫的社区发现算法研究

姓名
姓名拼音
FENG Defan
学号
11930382
学位类型
硕士
学位专业
0809 电子科学与技术
学科门类/专业学位类别
08 工学
导师
宋轩
导师单位
计算机科学与工程系
论文答辩日期
2022-05-08
论文提交日期
2022-06-15
学位授予单位
南方科技大学
学位授予地点
深圳
摘要
2019 新型冠状病毒自 2019 年开始在全世界范围内广泛传播,如何更好的抑制 其在各个地区内的爆发速度一度成为诸多研究者们的研究对象。而随着人们对于 这种病毒的了解日益深入,目前针对 2019 新型冠状病毒的防控研究需求逐渐从尽 可能的减少一个国家内的感染人数变成了提出一个精细程度更高的,能够尽可能
的减少无用防疫政策的精准防疫模式。这个课题主要构建了一个完整的针对 2019
新型冠状病毒的精准防疫系统,通过采用卡尔曼滤波,空间二分树等算法完成了针对防疫所需要的数据集的数据预处理,随后在栅格选取,流行病学模型以及小 世界模型的基础之上,搭建了一个精确度到达个人的 2019 新型冠状病毒疫情模拟 程序,并且在后续采用了一种结合了静态社区划分以及动态社区更新的社区发现 算法来完成模拟程序之中针对确诊患者的快速精准的追溯,从而在尽可能的减少 了感染的人数的同时最小化经济上的额外损失,实现了一套智能精准的防疫系统。
关键词
语种
中文
培养类别
独立培养
入学年份
2019
学位授予年份
2022-06
参考文献列表

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冯德帆. 基于轨迹数据精准防疫的社区发现算法研究[D]. 深圳. 南方科技大学,2022.
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