[1]田 锋,魏代俊.基于多层交通网络度-度距离模型的新冠肺炎传播研究[J].南京师大学报(自然科学版),2022,(02):91-97.[doi:10.3969/j.issn.1001-4616.2022.02.011]
 Tian Feng,Wei Daijun.Degree-Degree Distance Based on the Perspective of Multi-Layer Traffic Network COVID-19 Transmission Research[J].Journal of Nanjing Normal University(Natural Science Edition),2022,(02):91-97.[doi:10.3969/j.issn.1001-4616.2022.02.011]
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基于多层交通网络度-度距离模型的新冠肺炎传播研究()
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《南京师大学报(自然科学版)》[ISSN:1001-4616/CN:32-1239/N]

卷:
期数:
2022年02期
页码:
91-97
栏目:
·计算机科学与技术·
出版日期:
2022-05-15

文章信息/Info

Title:
Degree-Degree Distance Based on the Perspective of Multi-Layer Traffic Network COVID-19 Transmission Research
文章编号:
1001-4616(2022)02-0091-07
作者:
田 锋魏代俊
(湖北民族大学数学与统计学院,湖北 恩施 445000)
Author(s):
Tian FengWei Daijun
(School of Mathematics and Statistics,Hubei Minzu University,Enshi 445000,China)
关键词:
新冠肺炎度-度距离多层交通网络分层聚类
Keywords:
COVID-19degree-degree distancemulti-layer traffic networkhierarchical clustering
分类号:
O213
DOI:
10.3969/j.issn.1001-4616.2022.02.011
文献标志码:
A
摘要:
本文将单层网络度-度距离模型推广到多层网络,建立多层交通网络度-度距离模型,并基于该模型对湖北省内17个地级市(州)的新冠疫情传播进行研究分析. 主要贡献和结论为:(1)发现新冠疫情的传播在不同交通方式中存在较大差异;(2)按照多层网络度-度距离模型划分城市群聚类分析的结果与按确诊人数聚类结果的一致性很高.
Abstract:
In this paper,the degree-degree distance model of single-layer network was extended to multi-layer network of that and the degree-degree distance model of multi-layer traffic network was established. Based on this model,the transmission of COVID-19 in 17 prefecture-level cities(prefectures)in Hubei Province was analyzed. The main contributions and conclusions are as follows:(1)It was found that the transmission of COVID-19 was significantly different among different ways of transportation.(2)The results of urban cluster analysis based on the hierarchical network degree-degree distance model are in high agreement with the results of cluster analysis based on the number of confirmed patients.

参考文献/References:

[1] 武汉市卫健委. 武汉市卫健委关于当前我市肺炎疫情的情况通报[EB/OL].
[2019-12-31].
[2]唐丽,甄东,李倩. 基于泊松回归模型和注意力配置理论的新冠疫情防控研究[J]. 南京师大学报(自然科学版),2021,44(1):6-12.
[3]HUANG C,WANG Y,LI X,et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan,China[J]. The lancet,2020,395(10223):497-506.
[4]王建伟,崔秩玮,潘潇雄,等. 基于广义SEIR模型的新冠肺炎传播机制及干预效果仿真[J]. 科技导报,2020,38(22):130-138.
[5]ZHU N,ZHANG D,WANG W,et al. A novel coronavirus from patients with pneumonia in China,2019[J]. New England journal of medicine,2020,382(8):727-733.
[6]杜绍洪,李文烁,郑江溢,等. 基于BP神经网络与聚类分析的数学创新能力研究[J]. 南京师大学报(自然科学版),2019,42(2):23-29.
[7]许小可,文成,张光耀,等. 新冠肺炎爆发前期武汉外流人口的地理去向分布及影响[J]. 电子科技大学学报,2020,49(3):324-329.
[8]唐代旻,李响,赵子辉. 面向交通微观仿真的道路网络模型[J]. 南京师大学报(自然科学版),2016,39(4):38-43.
[9]孙皓宸,徐铭达,许小可,等. 基于真实人际接触数据的新冠肺炎校园传播与防控[J]. 电子科技大学学报,2020,49(3):399-407.
[10]丁莹,张健钦,杨木,等. 新冠疫情城市仿真模型及防控措施评价-以武汉市为例[J]. 清华大学学报(自然科学版),2021,61(12):10.
[11]LI T. Simulating the spread of epidemics in China on multi-layer transportation networks:Beyond COVID-19 in Wuhan[J]. Europhysics letters,2020,130(4):48002.
[12]第一财经:离开武汉的500多万人都去了哪里?大数据告诉你[EB/OL]. [2020-02-03].
[13]甄峰,王波.“大数据”热潮下人文地理学研究的再思考[J]. 地理研究,2015,34(5):803-811.
[14]王贤文,王虹茵,李清纯. 基于地理位置大数据的京津冀城市群短期人口流动研究[J]. 大连理工大学学报(社会科学版),2015,34(5):800-813.
[15]蒋小荣,汪胜兰. 中国地级市以上人口流动网络研究-基于百度迁徙大数据的分析[J]. 中国人口科学,2017(5):35-46.
[16]孟繁华. 基于复杂网络的供应链建模及其鲁棒性分析[D]. 保定:华北电力大学(河北),2009.
[17]邓世果. 基于复杂网络结构的中国航空网络重要性节点分析[J]. 中国物流与采购,2021(7):78-79.
[18]曹文静,刘小菲,韩卓,等. 新型冠状病毒肺炎疫情确诊病例的统计回归及自回归建模[J]. 物理学报,2020,69(9):40-46.
[19]王兴隆,朱丽纳,石宗北. 多层航线聚合网络建模及相关性分析[J]. 科学技术与工程,2020,20(3):1243-1249.
[20]唐三一,唐彪,BRAGAZZI N L,等. 新型冠状病毒肺炎疫情数据挖掘与离散随机传播动力学模型分析[J]. 中国科学:数学,2020,50(8):1071-1086.
[21]汪小帆,李翔,陈关荣. 复杂网络理论及其应用[M]. 北京:清华大学出版社,2006.
[22]ZHOU B,MENG X Y,STANLEY H E. Power-law distribution of degree-degree distance:a better representation of the scale-free property of complex networks[J]. Proceedings of the National Academy of Sciences,2020,117(26):14812-14818.
[23]XIE Y K,WANG Z. Transmission dynamics,global stability and control strategies of a modified SIS epidemic model on complex networks with an infective medium[J]. Mathematics and computers in simulation,2021,188:23-34.
[24]TANG B,LI Q,BRAGAZZI N L,et al. An updated estimation of the risk of transmission of the novel coronavirus(2019-nCov)[J]. Infectious disease modelling,2020,5:248-255.
[25]DONG Z H,CHEN Y Z,TRICCO T S,et al. Hunting for vital nodes in complex networks using local information[J]. Scientific reports,2021,11(1):9190.
[26]CHEN W,GEORGE F G,et al. A novel coronavirus outbreak of global health concern[J]. The lancet,2020,395(10223):470-473.
[27]WU J T,KATHY L,LEUNG G M. Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan,China:a modelling study[J]. The lancet,2020,395(10225):689-697.
[28]TANG B,XIA F,TANG S,et al. The effectiveness of quarantine and isolation determine the trend of the COVID-19 epidemic in the final phase of the current outbreak in China[J]. International journal of infectious diseases,2020,96:636-647.
[29]TIAN H,LIU Y,LI Y,et al. An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China[J]. Science,2020,368(6491):638-642.
[30]ZHANG L,HAI Y,DI W,et al. Solving a discrete multimodal transportation network design problem[J]. Transportation research part C emerging technologies,2014,49:73-86.

相似文献/References:

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备注/Memo

备注/Memo:
基金项目:国家自然科学基金项目(61763009).
通讯作者:魏代俊,博士,教授,研究方向:复杂网络、经济统计等方面的研究. E-mail:2001013@hbmy.edu.cn
更新日期/Last Update: 1900-01-01