首页 期刊 论文 学科刊群 资讯 加盟 关于
EN
image
Article(id=1207343632726725249, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1207343627223802520, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2406796, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1725897600000, receivedDateStr=2024-09-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1765782753402, onlineDateStr=2025-12-15, pubDate=1750176000000, pubDateStr=2025-06-18, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1765782753402, onlineIssueDateStr=2025-12-15, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1765782753402, creator=13701087609, updateTime=1765782753402, updator=13701087609, issue=Issue{id=1207343627223802520, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='17', pageStart='7023', pageEnd='7453', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1765782752085, creator=13701087609, updateTime=1765783816840, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1207348093192872694, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1207343627223802520, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1207348093192872695, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1207343627223802520, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=7405, endPage=7416, ext={EN=ArticleExt(id=1207343634479944334, articleId=1207343632726725249, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Characteristics of Airport Traffic Flow Fluctuation Range Based on Complex Networks: Taking the Beijing Daxing International Airport as an Example, columnId=1207343633745941130, journalTitle=Science Technology and Engineering, columnName=Papers-Aeronautics and Astronautics, runingTitle=null, highlight=null, articleAbstract=

Studying the characteristics of airport traffic flow fluctuation range is fundamental for efficient traffic management and control. Mastering these characteristics plays a crucial role in maintaining the stability and effectiveness of overall airport operations. Considering the irreversibility of time and the cumulative impact of traffic congestion, which occurs when airport traffic exceeds facility capacity within certain time intervals, a method for constructing an adaptive crossing network was proposed. From the perspective of complex network topology, both the overall characteristics of the network and the centrality of nodes were analyzed. The integrated centrality of nodes was calculated using the independent weighting coefficient method, enabling the identification of key time nodes that are core hubs of strong fluctuations within the network. The results show that the adaptive crossing network, mapped based on the traffic data from Beijing Daxing International Airport, exhibits characteristics of complexity and order, featuring scale-free properties, assortativity, and a distinct community structure. The time period from 21:20 to 22:25 (nodes 257~269) ranks highly across various centrality measures, indicating a significant fluctuation impact range, and thus, these nodes are identified as core hub nodes within the network. The integrated centrality synthesizes various topological centrality features of the network, and through quantitative analysis, effectively characterizes the strong fluctuation nodes within the network. This method provides a theoretical basis and practical reference for the optimization of airport traffic flow management and the study of abnormal fluctuations, offering a new perspective for enhancing airport operational efficiency and safety.

, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Xie ZHANG, Xin-yu ZHANG, Jun ZHANG), CN=ArticleExt(id=1207343637223019268, articleId=1207343632726725249, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=基于复杂网络的机场交通流量波动范围特征: 以北京大兴机场为例, columnId=1156262731373208516, journalTitle=科学技术与工程, columnName=论文·航空、航天, runingTitle=null, highlight=null, articleAbstract=研究机场交通流量的波动范围特征是进行高效流量管理及控制的基础,理解并掌握机场交通流量波动范围特征对维持整个机场交通运行的稳定性和有效性起着重要作用。通过考虑时间的不可逆性及在一定时段内机场流量大于设施容量所产生的拥堵量会累加影响在后续时间点上,提出自适应跨越网络的构建方法。从复杂网络拓扑特性角度出发,对网络的整体特征以及节点中心性进行分析,并应用独立性权系数法分别计算节点的综合中心度,识别网络中的强波动核心枢纽时间节点。结果表明:根据北京大兴机场流量数据映射得到的自适应跨越网络呈现复杂有序的特点,具有无标度特征,网络是同配的且有明显的社团结构;21:20—22:25(节点257~269)中在各中心度的排名均靠前,波动影响范围较大,属于网络中的核心枢纽节点;综合中心度归纳了网络的各种拓扑中心性特征,并对其进行定量分析后有效刻画了网络中的强波动节点。该方法为机场交通流量的优化管理和异常波动研究提供了理论依据和实践参考,为提升机场运行效率和安全性提供了新的视角。, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=M/n5dbRklgpEHbA4UlYM2A==, magXml=lqpnWPQDfmzIbNDnMwNbpQ==, pdfUrl=null, pdf=f5HExsgz4NcVVp+sdM48JA==, pdfFileSize=11696532, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=wUIEq3hI2QAJZMVwAugi8g==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=QhSb4se/MQL3JzOVJXujRQ==, mapNumber=null, authorCompany=null, fund=null, authors=

张勰(1981—),男,汉族,陕西咸阳人,博士,副研究员。研究方向:空中交通流特征分析。E-mail:。

, authorsList=张勰, 张鑫宇, 张钧)}, authors=[Author(id=1207400965410497132, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=xiezhang@cauc.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1207400965553103474, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, authorId=1207400965410497132, language=EN, stringName=Xie ZHANG, firstName=Xie, middleName=null, lastName=ZHANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1 College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1207400965645378167, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, authorId=1207400965410497132, language=CN, stringName=张勰, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1 中国民航大学空中交通管理学院, 天津 300300, bio={"content":"

张勰(1981—),男,汉族,陕西咸阳人,博士,副研究员。研究方向:空中交通流特征分析。E-mail:。

"}, bioImg=null, bioContent=

张勰(1981—),男,汉族,陕西咸阳人,博士,副研究员。研究方向:空中交通流特征分析。E-mail:。

, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1207400965192393306, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, xref=1, ext=[AuthorCompanyExt(id=1207400965196587611, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, companyId=1207400965192393306, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China), AuthorCompanyExt(id=1207400965209170525, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, companyId=1207400965192393306, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 中国民航大学空中交通管理学院, 天津 300300)])]), Author(id=1207400966895280767, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1207400967025304197, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, authorId=1207400966895280767, language=EN, stringName=Xin-yu ZHANG, firstName=Xin-yu, middleName=null, lastName=ZHANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1 College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1207400967142744716, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, authorId=1207400966895280767, language=CN, stringName=张鑫宇, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1 中国民航大学空中交通管理学院, 天津 300300, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1207400965192393306, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, xref=1, ext=[AuthorCompanyExt(id=1207400965196587611, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, companyId=1207400965192393306, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China), AuthorCompanyExt(id=1207400965209170525, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, companyId=1207400965192393306, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 中国民航大学空中交通管理学院, 天津 300300)])]), Author(id=1207400967243408017, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1207400967365042842, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, authorId=1207400967243408017, language=EN, stringName=Jun ZHANG, firstName=Jun, middleName=null, lastName=ZHANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=2 Air Traffic Management Department, Linyi International Airport, Linyi 276037, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1207400967453123233, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, authorId=1207400967243408017, language=CN, stringName=张钧, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=2 山东省机场集团临沂国际机场航务管理部, 临沂 276037, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1207400965301445217, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, xref=2, ext=[AuthorCompanyExt(id=1207400965309833827, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, companyId=1207400965301445217, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 Air Traffic Management Department, Linyi International Airport, Linyi 276037, China), AuthorCompanyExt(id=1207400965314028132, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, companyId=1207400965301445217, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 山东省机场集团临沂国际机场航务管理部, 临沂 276037)])])], keywords=[Keyword(id=1207400967620895403, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, orderNo=1, keyword=air transportation), Keyword(id=1207400967713170098, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, orderNo=2, keyword=network characteristics), Keyword(id=1207400967813833398, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, orderNo=3, keyword=complex networks), Keyword(id=1207400967906108092, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, orderNo=4, keyword=airport traffic flow), Keyword(id=1207400968031937218, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, orderNo=5, keyword=nonlinear time series analysis), Keyword(id=1207400968128406214, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, orderNo=1, keyword=航空运输), Keyword(id=1207400968224875210, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, orderNo=2, keyword=网络特征), Keyword(id=1207400968308761294, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, orderNo=3, keyword=复杂网络), Keyword(id=1207400968422007507, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, orderNo=4, keyword=机场交通流), Keyword(id=1207400968543642326, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, orderNo=5, keyword=非线性时间序列分析)], refs=[Reference(id=1207400973182542678, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2020, volume=49, issue=1, pageStart=24, pageEnd=35, url=null, language=null, rfNumber=[1], rfOrder=0, authorNames=韩敏, 任伟杰, 李柏松, journalName=信息与控制, refType=null, unstructuredReference=韩敏, 任伟杰, 李柏松, 等. 混沌时间序列分析与预测研究综述[J]. 信息与控制, 2020, 49(1): 24-35., articleTitle=混沌时间序列分析与预测研究综述, refAbstract=null), Reference(id=1207400973312566107, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2020, volume=49, issue=1, pageStart=24, pageEnd=35, url=null, language=null, rfNumber=[1], rfOrder=1, authorNames=Han Min, Ren Weijie, Li Baisong, journalName=Information and Control, refType=null, unstructuredReference=Han Min, Ren Weijie, Li Baisong, et al. Survey of chaotic time series analysis and prediction[J]. Information and Control, 2020, 49(1): 24-35., articleTitle=Survey of chaotic time series analysis and prediction, refAbstract=null), Reference(id=1207400973413229407, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2023, volume=51, issue=9, pageStart=2598, pageEnd=2622, url=null, language=null, rfNumber=[2], rfOrder=2, authorNames=李海林, 王杰, 周文浩, journalName=电子学报, refType=null, unstructuredReference=李海林, 王杰, 周文浩, 等. 时间序列复杂网络分析中的可视图方法研究综述[J]. 电子学报, 2023, 51(9): 2598-2622., articleTitle=时间序列复杂网络分析中的可视图方法研究综述, refAbstract=null), Reference(id=1207400973476143970, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2023, volume=51, issue=9, pageStart=2598, pageEnd=2622, url=null, language=null, rfNumber=[2], rfOrder=3, authorNames=Li Hailin, Wang Jie, Zhou Wenhao, journalName=Acta Electronica Sinica, refType=null, unstructuredReference=Li Hailin, Wang Jie, Zhou Wenhao, et al. A review of visibility graph methods research in time series complex network analysis[J]. Acta Electronica Sinica, 2023, 51(9): 2598-2622., articleTitle=A review of visibility graph methods research in time series complex network analysis, refAbstract=null), Reference(id=1207400973597778790, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2020, volume=50, issue=5, pageStart=61, pageEnd=65, url=null, language=null, rfNumber=[3], rfOrder=4, authorNames=王敏, 朱明, journalName=航空计算技术, refType=null, unstructuredReference=王敏, 朱明. 基于复杂网络理论的空中交通流时间序列分析[J]. 航空计算技术, 2020, 50(5): 61-65., articleTitle=基于复杂网络理论的空中交通流时间序列分析, refAbstract=null), Reference(id=1207400973660693353, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2020, volume=50, issue=5, pageStart=61, pageEnd=65, url=null, language=null, rfNumber=[3], rfOrder=5, authorNames=Wang Min, Zhu Ming, journalName=Aeronautical Computing Technology, refType=null, unstructuredReference=Wang Min, Zhu Ming. Time series analysis of air traffic flow based on complex network theory[J]. Aeronautical Computing Technology, 2020, 50(5): 61-65., articleTitle=Time series analysis of air traffic flow based on complex network theory, refAbstract=null), Reference(id=1207400973736190827, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2017, volume=52, issue=1, pageStart=171, pageEnd=178, url=null, language=null, rfNumber=[4], rfOrder=6, authorNames=王超, 郑旭芳, 王蕾, journalName=西南交通大学学报, refType=null, unstructuredReference=王超, 郑旭芳, 王蕾. 交汇航路空中交通流的非线性特征研究[J]. 西南交通大学学报, 2017, 52(1): 171-178., articleTitle=交汇航路空中交通流的非线性特征研究, refAbstract=null), Reference(id=1207400973849437038, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2017, volume=52, issue=1, pageStart=171, pageEnd=178, url=null, language=null, rfNumber=[4], rfOrder=7, authorNames=Wang Chao, Zheng Xufang, Wang Lei, journalName=Journal of Southwest Jiaotong University, refType=null, unstructuredReference=Wang Chao, Zheng Xufang, Wang Lei. Research on nonlinear characteristics of air traffic flows on converging air routes[J]. Journal of Southwest Jiaotong University, 2017, 52(1): 171-178., articleTitle=Research on nonlinear characteristics of air traffic flows on converging air routes, refAbstract=null), Reference(id=1207400973933323121, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2018, volume=35, issue=6, pageStart=81, pageEnd=85, url=null, language=null, rfNumber=[5], rfOrder=8, authorNames=王超, 朱明, journalName=计算机仿真, refType=null, unstructuredReference=王超, 朱明. 基于复杂网络表征ATF时间序列动力学特性[J]. 计算机仿真, 2018, 35(6): 81-85., articleTitle=基于复杂网络表征ATF时间序列动力学特性, refAbstract=null), Reference(id=1207400974130455413, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2018, volume=35, issue=6, pageStart=81, pageEnd=85, url=null, language=null, rfNumber=[5], rfOrder=9, authorNames=Wang Chao, Zhu Ming, journalName=Computer Simulation, refType=null, unstructuredReference=Wang Chao, Zhu Ming. Representation of air traffic flow time series dynamic characteristics based on complex network[J]. Computer Simulation, 2018, 35(6): 81-85., articleTitle=Representation of air traffic flow time series dynamic characteristics based on complex network, refAbstract=null), Reference(id=1207400974231118712, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2024, volume=24, issue=18, pageStart=7913, pageEnd=7920, url=null, language=null, rfNumber=[6], rfOrder=10, authorNames=张兆宁, 孟凡淑, journalName=科学技术与工程, refType=null, unstructuredReference=张兆宁, 孟凡淑. 基于复杂网络的多机场航班延误传播分析[J]. 科学技术与工程, 2024, 24(18): 7913-7920., articleTitle=基于复杂网络的多机场航班延误传播分析, refAbstract=null), Reference(id=1207400974306616186, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2024, volume=24, issue=18, pageStart=7913, pageEnd=7920, url=null, language=null, rfNumber=[6], rfOrder=11, authorNames=Zhang Zhaoning, Meng Fanshu, journalName=Science Technology and Engineering, refType=null, unstructuredReference=Zhang Zhaoning, Meng Fanshu. Complex network-based analysis of multi-airport flight delay propagation[J]. Science Technology and Engineering, 2024, 24(18): 7913-7920., articleTitle=Complex network-based analysis of multi-airport flight delay propagation, refAbstract=null), Reference(id=1207400974382113661, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2019, volume=787, issue=null, pageStart=1, pageEnd=97, url=null, language=null, rfNumber=[7], rfOrder=12, authorNames=Zou Y, Donner R V, Marwan N, journalName=Physics Reports, refType=null, unstructuredReference=Zou Y, Donner R V, Marwan N, et al. Complex network approaches to nonlinear time series analysis[J]. Physics Reports, 2019, 787: 1-97., articleTitle=Complex network approaches to nonlinear time series analysis, refAbstract=null), Reference(id=1207400974482776958, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2008, volume=105, issue=13, pageStart=4972, pageEnd=4975, url=null, language=null, rfNumber=[8], rfOrder=13, authorNames=Lacasa L, Luque B, Ballesteros F, journalName=Proceedings of the National Academy of Sciences, refType=null, unstructuredReference=Lacasa L, Luque B, Ballesteros F, et al. From time series to complex networks: the visibility graph[J]. Proceedings of the National Academy of Sciences, 2008, 105(13): 4972-4975., articleTitle=From time series to complex networks: the visibility graph, refAbstract=null), Reference(id=1207400974587634562, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2012, volume=60, issue=null, pageStart=589, pageEnd=623, url=null, language=null, rfNumber=[9], rfOrder=14, authorNames=Donner R V, Donges J F, journalName=Acta Geophys, refType=null, unstructuredReference=Donner R V, Donges J F. Visibility graph analysis of geophysical time series: potentials and possible pitfalls[J]. Acta Geophys, 2012, 60: 589-623., articleTitle=Visibility graph analysis of geophysical time series: potentials and possible pitfalls, refAbstract=null), Reference(id=1207400974679909253, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2009, volume=373, issue=46, pageStart=4246, pageEnd=4254, url=null, language=null, rfNumber=[10], rfOrder=15, authorNames=Marwan N, Donges J F, Zou Y, journalName=Physics Letters A, refType=null, unstructuredReference=Marwan N, Donges J F, Zou Y, et al. Complex network approach for recurrence analysis of time series[J]. Physics Letters A, 2009, 373(46): 4246-4254., articleTitle=Complex network approach for recurrence analysis of time series, refAbstract=null), Reference(id=1207400975862702981, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2011, volume=21, issue=null, pageStart=1019, pageEnd=1046, url=null, language=null, rfNumber=[11], rfOrder=16, authorNames=Donner R V, Small M, Donges J F, journalName=International Journal of Bifurcation and Chaos, refType=null, unstructuredReference=Donner R V, Small M, Donges J F, et al. Recurrence-based time series analysis by means of complex network methods[J]. International Journal of Bifurcation and Chaos, 2011, 21: 1019-1046., articleTitle=Recurrence-based time series analysis by means of complex network methods, refAbstract=null), Reference(id=1207400975954977672, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2005, volume=15, issue=null, pageStart=3467, pageEnd=3480, url=null, language=null, rfNumber=[12], rfOrder=17, authorNames=Nicolis G, Cantu A G, Nicolis C, journalName=International Journal of Bifurcation and Chaos, refType=null, unstructuredReference=Nicolis G, Cantu A G, Nicolis C. Dynamical aspects of interaction networks[J]. International Journal of Bifurcation and Chaos, 2005, 15: 3467-3480., articleTitle=Dynamical aspects of interaction networks, refAbstract=null), Reference(id=1207400976026280840, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2017, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[13], rfOrder=18, authorNames=中华人民共和国交通运输部, journalName=民用航空空中交通管理规则, refType=null, unstructuredReference=中华人民共和国交通运输部. 民用航空空中交通管理规则[S]. 北京: 中华人民共和国交通运输部, 2017., articleTitle=null, refAbstract=null), Reference(id=1207400976135332745, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2017, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[13], rfOrder=19, authorNames=Ministry of transport of the People's Republic of China, journalName=Civil aviation air traffic management regulations, refType=null, unstructuredReference=Ministry of transport of the People's Republic of China. Civil aviation air traffic management regulations[S]. Beijing: Ministry of Transport of the People's Republic of China, 2017., articleTitle=null, refAbstract=null), Reference(id=1207400976244384650, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2018, volume=503, issue=null, pageStart=560, pageEnd=571, url=null, language=null, rfNumber=[14], rfOrder=20, authorNames=Liu H Z, Zhang X C, Zhang X, journalName=Physica A: Statistical Mechanics and its Applications, refType=null, unstructuredReference=Liu H Z, Zhang X C, Zhang X. Exploring dynamic evolution and fluctuation characteristics of air traffic flow volume time series: a single waypoint case[J]. Physica A: Statistical Mechanics and its Applications, 2018, 503: 560-571., articleTitle=Exploring dynamic evolution and fluctuation characteristics of air traffic flow volume time series: a single waypoint case, refAbstract=null), Reference(id=1207400976319882125, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2022, volume=22, issue=6, pageStart=244, pageEnd=257, url=null, language=null, rfNumber=[15], rfOrder=21, authorNames=张勰, 肖恩媛, 刘宏志, journalName=交通运输系统工程与信息, refType=null, unstructuredReference=张勰, 肖恩媛, 刘宏志, 等. 基于有限穿越可视图的进场航班流量波动特性研究[J]. 交通运输系统工程与信息, 2022, 22(6): 244-257., articleTitle=基于有限穿越可视图的进场航班流量波动特性研究, refAbstract=null), Reference(id=1207400976407962510, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2022, volume=22, issue=6, pageStart=244, pageEnd=257, url=null, language=null, rfNumber=[15], rfOrder=22, authorNames=Zhang Xie, Xiao Enyuan, Liu Hongzhi, journalName=Journal of Transportation Systems Engineering and Information Technology, refType=null, unstructuredReference=Zhang Xie, Xiao Enyuan, Liu Hongzhi, et al. Fluctuation characteristics of arrival flight flow based on limited penetrable visibility graph[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(6): 244-257., articleTitle=Fluctuation characteristics of arrival flight flow based on limited penetrable visibility graph, refAbstract=null), Reference(id=1207400976512820114, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2019, volume=531, issue=null, pageStart=121790, pageEnd=null, url=null, language=null, rfNumber=[16], rfOrder=23, authorNames=Zhang X, Liu H Z, Zhao Y, journalName=Physica A: Statistical Mechanics and Its Applications, refType=null, unstructuredReference=Zhang X, Liu H Z, Zhao Y, et al. Multifractal detrended fluctuation analysis on air traffic flow time series: a single airport case[J]. Physica A: Statistical Mechanics and Its Applications, 2019, 531: 121790., articleTitle=Multifractal detrended fluctuation analysis on air traffic flow time series: a single airport case, refAbstract=null), Reference(id=1207400976609289107, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2020, volume=545, issue=null, pageStart=123585, pageEnd=null, url=null, language=null, rfNumber=[17], rfOrder=24, authorNames=Liu H Z, Zhang X C, Zhang X, journalName=Physica A: Statistical Mechanics and Its Applications, refType=null, unstructuredReference=Liu H Z, Zhang X C, Zhang X. Multiscale multifractal analysis on air traffic flow time series: a single airport departure flight case[J]. Physica A: Statistical Mechanics and Its Applications, 2020, 545: 123585., articleTitle=Multiscale multifractal analysis on air traffic flow time series: a single airport departure flight case, refAbstract=null), Reference(id=1207400976684786583, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2020, volume=548, issue=null, pageStart=124485, pageEnd=null, url=null, language=null, rfNumber=[18], rfOrder=25, authorNames=Liu H Z, Zhang X C, Zhang X, journalName=Physica A: Statistical Mechanics and Its Applications, refType=null, unstructuredReference=Liu H Z, Zhang X C, Zhang X. Multiscale complexity analysis on airport air traffic flow volume time series[J]. Physica A: Statistical Mechanics and Its Applications, 2020, 548: 124485., articleTitle=Multiscale complexity analysis on airport air traffic flow volume time series, refAbstract=null), Reference(id=1207400976798032792, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2022, volume=165, issue=null, pageStart=112795, pageEnd=null, url=null, language=null, rfNumber=[19], rfOrder=26, authorNames=Liu H Z, Zhang X, Hu H, journalName=Chaos, Solitons & Fractals, refType=null, unstructuredReference=Liu H Z, Zhang X, Hu H, et al. Exploring the impact of flow values on multiscale complexity quantification of airport flight flow fluctuations[J]. Chaos, Solitons & Fractals, 2022, 165: 112795., articleTitle=Exploring the impact of flow values on multiscale complexity quantification of airport flight flow fluctuations, refAbstract=null), Reference(id=1207400976890307482, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2023, volume=23, issue=31, pageStart=13482, pageEnd=13491, url=null, language=null, rfNumber=[20], rfOrder=27, authorNames=姜敏勤, 石小晶, 杨钰, journalName=科学技术与工程, refType=null, unstructuredReference=姜敏勤, 石小晶, 杨钰, 等. 基于节点重要度动态评估的复杂网络级联失效分析[J]. 科学技术与工程, 2023, 23(31): 13482-13491., articleTitle=基于节点重要度动态评估的复杂网络级联失效分析, refAbstract=null), Reference(id=1207400976978387867, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2023, volume=23, issue=31, pageStart=13482, pageEnd=13491, url=null, language=null, rfNumber=[20], rfOrder=28, authorNames=Jiang Minqin, Shi Xiaojing, Yang Yu, journalName=Science Technology and Engineering, refType=null, unstructuredReference=Jiang Minqin, Shi Xiaojing, Yang Yu, et al. Complex network cascade failure analysis based on dynamic evaluation of node importance[J]. Science Technology and Engineering, 2023, 23(31): 13482-13491., articleTitle=Complex network cascade failure analysis based on dynamic evaluation of node importance, refAbstract=null), Reference(id=1207400977104216989, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2021, volume=21, issue=36, pageStart=15669, pageEnd=15673, url=null, language=null, rfNumber=[21], rfOrder=29, authorNames=徐开俊, 肖成坤, 杨泳, journalName=科学技术与工程, refType=null, unstructuredReference=徐开俊, 肖成坤, 杨泳, 等. 基于复杂网络理论的中国城市航空网络有向加权分析[J]. 科学技术与工程, 2021, 21(36): 15669-15673., articleTitle=基于复杂网络理论的中国城市航空网络有向加权分析, refAbstract=null), Reference(id=1207400977192297373, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2021, volume=21, issue=36, pageStart=15669, pageEnd=15673, url=null, language=null, rfNumber=[21], rfOrder=30, authorNames=Xu Kaijun, Xiao Chengkun, Yang Yong, journalName=Science Technology and Engineering, refType=null, unstructuredReference=Xu Kaijun, Xiao Chengkun, Yang Yong, et al. Directed weighted analysis of domestic urban aviation network based on complex network theory[J]. Science Technology and Engineering, 2021, 21(36): 15669-15673., articleTitle=Directed weighted analysis of domestic urban aviation network based on complex network theory, refAbstract=null), Reference(id=1207400977305543582, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2023, volume=23, issue=18, pageStart=8002, pageEnd=8010, url=null, language=null, rfNumber=[22], rfOrder=31, authorNames=张瑞, 朱春彦, 王琼, journalName=科学技术与工程, refType=null, unstructuredReference=张瑞, 朱春彦, 王琼, 等. 基于复杂网络的中国四大机场群多极航线网络结构特征分析[J]. 科学技术与工程, 2023, 23(18): 8002-8010., articleTitle=基于复杂网络的中国四大机场群多极航线网络结构特征分析, refAbstract=null), Reference(id=1207400977372652447, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2023, volume=23, issue=18, pageStart=8002, pageEnd=8010, url=null, language=null, rfNumber=[22], rfOrder=32, authorNames=Zhang Rui, Zhu Chunyan, Wang Qiong, journalName=Science Technology and Engineering, refType=null, unstructuredReference=Zhang Rui, Zhu Chunyan, Wang Qiong, et al. Analysis on the characteristics of airline network in China's four major multiple-airport systems based on complex network[J]. Science Technology and Engineering, 2023, 23(18): 8002-8010., articleTitle=Analysis on the characteristics of airline network in China's four major multiple-airport systems based on complex network, refAbstract=null), Reference(id=1207400977477510048, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2023, volume=32, issue=7, pageStart=24, pageEnd=35, url=null, language=null, rfNumber=[23], rfOrder=33, authorNames=李振福, 王紫荆, journalName=世界地理研究, refType=null, unstructuredReference=李振福, 王紫荆. 不同运输方式下大北极综合交通运输网络特性研究[J]. 世界地理研究, 2023, 32(7): 24-35., articleTitle=不同运输方式下大北极综合交通运输网络特性研究, refAbstract=null), Reference(id=1207400977557201824, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, doi=null, pmid=null, pmcid=null, year=2023, volume=32, issue=7, pageStart=24, pageEnd=35, url=null, language=null, rfNumber=[23], rfOrder=34, authorNames=Li Zhenfu, Wang Zijing, journalName=World Regional Studies, refType=null, unstructuredReference=Li Zhenfu, Wang Zijing. Research on the characteristics of Pan Arctic comprehensive transportation network under different transportation mode[J]. World Regional Studies, 2023, 32(7): 24-35., articleTitle=Research on the characteristics of Pan Arctic comprehensive transportation network under different transportation mode, refAbstract=null)], funds=[Fund(id=1207400972859581260, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, awardId=U2133210, language=CN, fundingSource=国家自然科学基金联合基金(U2133210), fundOrder=null, country=null), Fund(id=1207400972939273037, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, awardId=312202YY02, language=CN, fundingSource=中央高校基本科研业务费专项资金(312202YY02), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1207400965192393306, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, xref=1, ext=[AuthorCompanyExt(id=1207400965196587611, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, companyId=1207400965192393306, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China), AuthorCompanyExt(id=1207400965209170525, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, companyId=1207400965192393306, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 中国民航大学空中交通管理学院, 天津 300300)]), AuthorCompany(id=1207400965301445217, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, xref=2, ext=[AuthorCompanyExt(id=1207400965309833827, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, companyId=1207400965301445217, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 Air Traffic Management Department, Linyi International Airport, Linyi 276037, China), AuthorCompanyExt(id=1207400965314028132, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, companyId=1207400965301445217, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 山东省机场集团临沂国际机场航务管理部, 临沂 276037)])], figs=[ArticleFig(id=1207400968765940447, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, label=Fig.1, caption=Illustration of edge connections, figureFileSmall=4OC1ljf9EQsNjrWpm/m97A==, figureFileBig=1MVfErnNNGywu2GgXZgOzg==, tableContent=null), ArticleFig(id=1207400968866603749, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, label=图1, caption=连边示意图, figureFileSmall=4OC1ljf9EQsNjrWpm/m97A==, figureFileBig=1MVfErnNNGywu2GgXZgOzg==, tableContent=null), ArticleFig(id=1207400969009210092, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, label=Fig.2, caption=Time series of air traffic flow, figureFileSmall=4HSTTEzD4xz+lNBshRPn5g==, figureFileBig=sP0HWSPkYdjPtb0xweJE5Q==, tableContent=null), ArticleFig(id=1207400969097290481, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, label=图2, caption=空中交通流量时间序列, figureFileSmall=4HSTTEzD4xz+lNBshRPn5g==, figureFileBig=sP0HWSPkYdjPtb0xweJE5Q==, tableContent=null), ArticleFig(id=1207400969206342390, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, label=Fig.3, caption=Adaptive crossing network of traffic flow fluctuation range, figureFileSmall=wLb/XlyKMlrWOzAQgzWHoA==, figureFileBig=+3e27JFqcnHhVjIXeh1J9w==, tableContent=null), ArticleFig(id=1207400969332171515, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, label=图3, caption=流量波动自适应跨越网络, figureFileSmall=wLb/XlyKMlrWOzAQgzWHoA==, figureFileBig=+3e27JFqcnHhVjIXeh1J9w==, tableContent=null), ArticleFig(id=1207400969411863293, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, label=Fig.4, caption=Degree distribution of the network, figureFileSmall=k6QsXRNdO4mjLjlsF2Vt/w==, figureFileBig=5/GfgzDOvR5voZbxE1wbcA==, tableContent=null), ArticleFig(id=1207400969516720897, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, label=图4, caption=网络的度分布, figureFileSmall=k6QsXRNdO4mjLjlsF2Vt/w==, figureFileBig=5/GfgzDOvR5voZbxE1wbcA==, tableContent=null), ArticleFig(id=1207400969680298757, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, label=Fig.5, caption=In-degree and out-degree centrality of each node, figureFileSmall=U1irzq55byDSjvQ7dYAAHA==, figureFileBig=LEgBNpGZSoaP+Y+60TNPLw==, tableContent=null), ArticleFig(id=1207400969827099403, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, label=图5, caption=各节点入度、出度中心度, figureFileSmall=U1irzq55byDSjvQ7dYAAHA==, figureFileBig=LEgBNpGZSoaP+Y+60TNPLw==, tableContent=null), ArticleFig(id=1207400969940345616, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, label=Fig.6, caption=Ranking of high in-degree and out-degree hub nodes (taking the top 15 as an example), figureFileSmall=qVCNwCdRGe4jJJ3IGE/6Rg==, figureFileBig=2kgewIxACUMUN0Gc0R50Tw==, tableContent=null), ArticleFig(id=1207400970053591829, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, label=图6, caption=高入度、出度枢纽节点排名(以前15名为例), figureFileSmall=qVCNwCdRGe4jJJ3IGE/6Rg==, figureFileBig=2kgewIxACUMUN0Gc0R50Tw==, tableContent=null), ArticleFig(id=1207400970133283611, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, label=Fig.7, caption=All possible connection relationships of a node in the network, figureFileSmall=rlSUNaIcmi2lysL1km8rjw==, figureFileBig=LRrhX7IrlyQ/CJ7n6X/4gA==, tableContent=null), ArticleFig(id=1207400970212975389, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, label=图7, caption=网络中某节点所有可能的连接关系, figureFileSmall=rlSUNaIcmi2lysL1km8rjw==, figureFileBig=LRrhX7IrlyQ/CJ7n6X/4gA==, tableContent=null), ArticleFig(id=1207400971437712160, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, label=Fig.8, caption=Ranking of node eigenvector centrality, figureFileSmall=NnwTA06W9RrS5Scv7QFepg==, figureFileBig=6/l9cZHFhg9O9xWdCVp9Wg==, tableContent=null), ArticleFig(id=1207400971538375460, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, label=图8, caption=各节点特征向量中心度排名, figureFileSmall=NnwTA06W9RrS5Scv7QFepg==, figureFileBig=6/l9cZHFhg9O9xWdCVp9Wg==, tableContent=null), ArticleFig(id=1207400971626455848, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, label=Fig.9, caption=Network diagram of core nodes (shell values in parentheses), figureFileSmall=9TSVZFMm9Lxix24o1sx3uQ==, figureFileBig=/ld4OP/N8l1RHVBXeX8nqA==, tableContent=null), ArticleFig(id=1207400971748090667, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, label=图9, caption=3、4核节点网络图(括号内为shell值), figureFileSmall=9TSVZFMm9Lxix24o1sx3uQ==, figureFileBig=/ld4OP/N8l1RHVBXeX8nqA==, tableContent=null), ArticleFig(id=1207400971823588143, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, label=Fig.10, caption=Ranking of node core-shell centrality, figureFileSmall=08yD3LWp18npSa40CEdFqw==, figureFileBig=/ZfGY3p45FXzAryjS7r+JA==, tableContent=null), ArticleFig(id=1207400971911668531, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, label=图10, caption=各节点core-shell中心度排名, figureFileSmall=08yD3LWp18npSa40CEdFqw==, figureFileBig=/ZfGY3p45FXzAryjS7r+JA==, tableContent=null), ArticleFig(id=1207400972020720439, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, label=Fig.11, caption=Statistical results of integrated centrality for each node, figureFileSmall=xPBusX0p2DA7JP2DcLKOiQ==, figureFileBig=176XldLquB7I5lJ/nIQPHw==, tableContent=null), ArticleFig(id=1207400972087829305, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, label=图11, caption=各节点综合中心度统计结果, figureFileSmall=xPBusX0p2DA7JP2DcLKOiQ==, figureFileBig=176XldLquB7I5lJ/nIQPHw==, tableContent=null), ArticleFig(id=1207400972192686909, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, label=Table 1, caption=

Community structure in the network

, figureFileSmall=null, figureFileBig=null, tableContent=
社团
(包含节点数)		 社团内节点 社团
(包含节点数)		 社团内节点
1(共19个) 1~19 11(共11个) 164~174
2(共18个) 20~37 12(共12个) 175~186
3(共16个) 38~53 13(共11个) 187~197
4(共19个) 54~72 14(共21个) 198~218
5(共18个) 73~90 15(共12个) 219~230
6(共12个) 91~102 16(共11个) 231~241
7(共14个) 103~116 17(共15个) 242~256
8(共12个) 117~128 18(共18个) 257~274
9(共17个) 129~145 19(共14个) 275~288
10(共18个) 146~163
), ArticleFig(id=1207400972310127425, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, label=表1, caption=

网络中的社团结构

, figureFileSmall=null, figureFileBig=null, tableContent=
社团
(包含节点数)		 社团内节点 社团
(包含节点数)		 社团内节点
1(共19个) 1~19 11(共11个) 164~174
2(共18个) 20~37 12(共12个) 175~186
3(共16个) 38~53 13(共11个) 187~197
4(共19个) 54~72 14(共21个) 198~218
5(共18个) 73~90 15(共12个) 219~230
6(共12个) 91~102 16(共11个) 231~241
7(共14个) 103~116 17(共15个) 242~256
8(共12个) 117~128 18(共18个) 257~274
9(共17个) 129~145 19(共14个) 275~288
10(共18个) 146~163
), ArticleFig(id=1207400972507259715, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=EN, label=Table 2, caption=

Clustering coefficients of key nodes

, figureFileSmall=null, figureFileBig=null, tableContent=
节点 聚类系数 节点 聚类系数
104 0.5 196 0.5
113 0.5 201 0.5
118 0.5 207 0.5
121 0.5 211 0.5
122 0.5 220 0.5
130 0.5 222 0.5
136 0.5 224 0.5
139 0.5 227 0.5
142 0.5 236 0.5
162 0.5 238 0.5
166 0.5 243 0.5
168 0.5 260 0.5
173 0.5 264 0.5
183 0.5 268 0.5
188 0.5 276 0.5
194 0.5
), ArticleFig(id=1207400972624700230, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1207343632726725249, language=CN, label=表2, caption=

主要节点的聚类系数

, figureFileSmall=null, figureFileBig=null, tableContent=
节点 聚类系数 节点 聚类系数
104 0.5 196 0.5
113 0.5 201 0.5
118 0.5 207 0.5
121 0.5 211 0.5
122 0.5 220 0.5
130 0.5 222 0.5
136 0.5 224 0.5
139 0.5 227 0.5
142 0.5 236 0.5
162 0.5 238 0.5
166 0.5 243 0.5
168 0.5 260 0.5
173 0.5 264 0.5
183 0.5 268 0.5
188 0.5 276 0.5
194 0.5
)], attaches=null, journal=Journal(id=1146119176004939786, delFlag=0, nameCn=科学技术与工程, nameEn=Science Technology and Engineering, nameHistory1=null, nameHistory2=null, issn=1671-1815, eissn=, cn=11-4688/T, coden=null, periodic=4, language=CN, oaType=是, ccby=null, superviseOffice=null, ownerOffice=null, pubOffice=null, editorOffice=null, officeType=null, aims=null, clcCode=null, officeProv=null, officeCity=null, officeAddr=null, officeZip=null, officeEmail=null, officePhone=null, editDirector=null, officeDirector=null, officeDirectorPhone=null, officeStaffNum=null, officeEmpNum=null, coverPicUrl=UKU/O7GSka5polgCTkbIIw==, journalPrice=null, startedYear=null, abbrevIsoEn=Sci Technol Eng, journalRemark=null, publicationField=null, createdTime=null, updatedTime=1754445529766, createdBy=null, updatedBy=13701087609, firstLetterCn=S, firstLetterEn=S, subjectCode=Natural Sciences, subjectName=自然科学, subjectCodeEn=Natural Sciences, subjectNameEn=null, picCn=UKU/O7GSka5polgCTkbIIw==, picEn=5hwlULoNwcbj3xUmVi9MAQ==, jcr=null, cjcr=null, exts=[JournalExt(id=1159791870395564357, language=CN, name=科学技术与工程, nameHistory1=null, nameHistory2=null, managedBy=, sponsoredBy=, publishedBy=, editorOffice=, officeProv=null, officeCity=null, officeAddr=, officeZip=, editDirector=null, officeDirector=null, officePhone=null, coverPicUrl=null, journalRemark=, submitArticleUrl=null, websiteUrl=http://www.stae.com.cn/jsygc/home, createdTime=1754445529793, updatedTime=1754445529793, createdBy=13701087609, updatedBy=13701087609, submissionGuidelinesUrl=http://www.stae.com.cn/jsygc/site/menus/20090429150146001, submissionAuthorUrl=http://www.stae.com.cn/jsygc/author/login, submissionEditorUrl=http://www.stae.com.cn/jsygc/editor/login, submissionReviewUrl=http://www.stae.com.cn/jsygc/reviewer/login, submissionCeEditorUrl=, submissionAeEditorUrl=, option={"copyright":""}), JournalExt(id=1159791870441701702, language=EN, name=Science Technology and Engineering, nameHistory1=null, nameHistory2=null, managedBy=, sponsoredBy=, publishedBy=, editorOffice=, officeProv=null, officeCity=null, officeAddr=, officeZip=, editDirector=null, officeDirector=null, officePhone=null, coverPicUrl=null, journalRemark=, submitArticleUrl=null, websiteUrl=http://www.stae.com.cn/jsygc/home, createdTime=1754445529804, updatedTime=1754445529804, createdBy=13701087609, updatedBy=13701087609, submissionGuidelinesUrl=, submissionAuthorUrl=http://www.stae.com.cn/jsygc/author/login, submissionEditorUrl=http://www.stae.com.cn/jsygc/editor/login, submissionReviewUrl=http://www.stae.com.cn/jsygc/reviewer/login, submissionCeEditorUrl=, submissionAeEditorUrl=, option={"copyright":""})], databaseList=null, tenantJournalId=1146123166801305609, websiteList=[Website(id=1148243202391400884, webName=null, webTitle=null, webDomain=null, webCopyrigh=null, webIpcNo=null, seoTitle=null, seoKeywords=null, seoDescription=null, tenantJournalId=null, journalId=1146123166801305609, journalNameCn=null, journalNameEn=null, grayFlag=null, tenantId=1146029695717560320, platformId=null, journalGroupId=null, journalGroupNameCn=null, journalGroupNameEn=null, type=1, domain=https://castjournals.cast.org.cn/joweb/kxjsygc/CN, language=CN, createTime=1751692112777, createBy=18614031015, updateTime=1753520965431, updateBy=18614031015, name=科学技术与工程-中文站点, tplId=1146099689490845704, title=科学技术与工程, delFlag=0, indexPage=/home, props=[WebsiteProps(id=1148622798802673703, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1148243202391400884, code=articleTextType, value=kx, createTime=1751782615614, updateTime=1751782615614, creator=18614031015, updator=18614031015), WebsiteProps(id=1148622798781702180, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1148243202391400884, code=banner, value=null, createTime=1751782615609, updateTime=1751782615609, creator=18614031015, updator=18614031015), WebsiteProps(id=1148622798769119267, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1148243202391400884, code=logo, value=https://castjournals.cast.org.cn/joweb/kjdb/CN/file/pic?fileId=j86gbwi+p0Idkyl5SzIlmQ==, createTime=1751782615606, updateTime=1751782615606, creator=18614031015, updator=18614031015), WebsiteProps(id=1148622798794285094, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1148243202391400884, code=picServerUrl, value=https://castjournals.cast.org.cn/joweb/kjdb/CN/file/pic, createTime=1751782615612, updateTime=1751782615612, creator=18614031015, updator=18614031015), WebsiteProps(id=1148622798790090789, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1148243202391400884, code=staticResourcePath, value=https://castjournals.cast.org.cn/joweb/cast_kjdb_cn_619/, createTime=1751782615611, updateTime=1751782615611, creator=18614031015, updator=18614031015)]), Website(id=1155914124811976731, webName=null, webTitle=null, webDomain=null, webCopyrigh=null, webIpcNo=null, seoTitle=null, seoKeywords=null, seoDescription=null, tenantJournalId=null, journalId=1146123166801305609, journalNameCn=null, journalNameEn=null, grayFlag=null, tenantId=1146029695717560320, platformId=null, journalGroupId=null, journalGroupNameCn=null, journalGroupNameEn=null, type=1, domain=https://castjournals.cast.org.cn/joweb/kxjsygc/EN, language=EN, createTime=1753521003206, createBy=18614031015, updateTime=1753521003206, updateBy=18614031015, name=科学技术与工程-英文站点, tplId=1146101810881728533, title=Science Technology and Engineering, delFlag=0, indexPage=/home, props=[WebsiteProps(id=1155914371227308235, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1155914124811976731, code=articleTextType, value=kx, createTime=1753521061952, updateTime=1753521061952, creator=18614031015, updator=18614031015), WebsiteProps(id=1155914371210531016, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1155914124811976731, code=banner, value=null, createTime=1753521061947, updateTime=1753521061947, creator=18614031015, updator=18614031015), WebsiteProps(id=1155914371202142407, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1155914124811976731, code=logo, value=https://castjournals.cast.org.cn/joweb/kjdb/CN/file/pic?fileId=j86gbwi+p0Idkyl5SzIlmQ==, createTime=1753521061945, updateTime=1753521061945, creator=18614031015, updator=18614031015), WebsiteProps(id=1155914371223113930, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1155914124811976731, code=picServerUrl, value=https://castjournals.cast.org.cn/joweb/kjdb/CN/file/pic, createTime=1753521061950, updateTime=1753521061950, creator=18614031015, updator=18614031015), WebsiteProps(id=1155914371218919625, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1155914124811976731, code=staticResourcePath, value=https://castjournals.cast.org.cn/joweb/cast_kjdb_cn_619/, createTime=1753521061949, updateTime=1753521061949, creator=18614031015, updator=18614031015)])], journalTitle=科学技术与工程, weixinUrl=null, journalUrl=null, iacademicId=null, status=0, seqNo=null, journalTitleEn=Science Technology and Engineering, journalPhotoCn=UKU/O7GSka5polgCTkbIIw==, journalPhotoEn=5hwlULoNwcbj3xUmVi9MAQ==, journalFirstLetter=S, journalRecommend=null, journalNew=null, journalCollection=null, jcrJf=null, cjcrJf=null, jcrJfStr=null, cjcrJfStr=null, submissionFirstDecision=null, sciSubjectClassification=null, casSubjectClassification=null, citeScore=null, totalCitationFrequency=null, icpCode=null, psCode=null, advertisingLicenseCode=null, copyrightInformation=null, country=null, option=null, provinceCode=null, provinceName=null, collectFlag=false), detailUrlCn=https://castjournals.cast.org.cn/joweb/kxjsygc/CN/10.12404/j.issn.1671-1815.2406796, detailUrlEn=https://castjournals.cast.org.cn/joweb/kxjsygc/EN/10.12404/j.issn.1671-1815.2406796, pdfUrlCn=https://castjournals.cast.org.cn/joweb/kxjsygc/CN/PDF/10.12404/j.issn.1671-1815.2406796, pdfUrlEn=https://castjournals.cast.org.cn/joweb/kxjsygc/EN/PDF/10.12404/j.issn.1671-1815.2406796, aliStartDate=null, aliEndDate=null, collectionFlag=false, citedCount=null, citedUrl=null, reference=null)
收藏切换
基于复杂网络的机场交通流量波动范围特征: 以北京大兴机场为例
收藏切换
PDF下载
张勰 1 , 张鑫宇 1 , 张钧 2
科学技术与工程 | 论文·航空、航天 2025,25(17): 7405-7416
收起
收藏切换
科学技术与工程 | 论文·航空、航天 2025, 25(17): 7405-7416
基于复杂网络的机场交通流量波动范围特征: 以北京大兴机场为例
全屏
张勰1 , 张鑫宇1, 张钧2
作者信息
  • 1 中国民航大学空中交通管理学院, 天津 300300
  • 2 山东省机场集团临沂国际机场航务管理部, 临沂 276037

    • 张勰(1981—),男,汉族,陕西咸阳人,博士,副研究员。研究方向:空中交通流特征分析。E-mail:。

Characteristics of Airport Traffic Flow Fluctuation Range Based on Complex Networks: Taking the Beijing Daxing International Airport as an Example
Xie ZHANG1 , Xin-yu ZHANG1, Jun ZHANG2
Affiliations
  • 1 College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China
  • 2 Air Traffic Management Department, Linyi International Airport, Linyi 276037, China
出版时间: 2025-06-18 doi: 10.12404/j.issn.1671-1815.2406796
文章导航
收藏切换
摘要
收起
研究机场交通流量的波动范围特征是进行高效流量管理及控制的基础,理解并掌握机场交通流量波动范围特征对维持整个机场交通运行的稳定性和有效性起着重要作用。通过考虑时间的不可逆性及在一定时段内机场流量大于设施容量所产生的拥堵量会累加影响在后续时间点上,提出自适应跨越网络的构建方法。从复杂网络拓扑特性角度出发,对网络的整体特征以及节点中心性进行分析,并应用独立性权系数法分别计算节点的综合中心度,识别网络中的强波动核心枢纽时间节点。结果表明:根据北京大兴机场流量数据映射得到的自适应跨越网络呈现复杂有序的特点,具有无标度特征,网络是同配的且有明显的社团结构;21:20—22:25(节点257~269)中在各中心度的排名均靠前,波动影响范围较大,属于网络中的核心枢纽节点;综合中心度归纳了网络的各种拓扑中心性特征,并对其进行定量分析后有效刻画了网络中的强波动节点。该方法为机场交通流量的优化管理和异常波动研究提供了理论依据和实践参考,为提升机场运行效率和安全性提供了新的视角。
航空运输  /  网络特征  /  复杂网络  /  机场交通流  /  非线性时间序列分析

Studying the characteristics of airport traffic flow fluctuation range is fundamental for efficient traffic management and control. Mastering these characteristics plays a crucial role in maintaining the stability and effectiveness of overall airport operations. Considering the irreversibility of time and the cumulative impact of traffic congestion, which occurs when airport traffic exceeds facility capacity within certain time intervals, a method for constructing an adaptive crossing network was proposed. From the perspective of complex network topology, both the overall characteristics of the network and the centrality of nodes were analyzed. The integrated centrality of nodes was calculated using the independent weighting coefficient method, enabling the identification of key time nodes that are core hubs of strong fluctuations within the network. The results show that the adaptive crossing network, mapped based on the traffic data from Beijing Daxing International Airport, exhibits characteristics of complexity and order, featuring scale-free properties, assortativity, and a distinct community structure. The time period from 21:20 to 22:25 (nodes 257~269) ranks highly across various centrality measures, indicating a significant fluctuation impact range, and thus, these nodes are identified as core hub nodes within the network. The integrated centrality synthesizes various topological centrality features of the network, and through quantitative analysis, effectively characterizes the strong fluctuation nodes within the network. This method provides a theoretical basis and practical reference for the optimization of airport traffic flow management and the study of abnormal fluctuations, offering a new perspective for enhancing airport operational efficiency and safety.

air transportation  /  network characteristics  /  complex networks  /  airport traffic flow  /  nonlinear time series analysis
张勰, 张鑫宇, 张钧. 基于复杂网络的机场交通流量波动范围特征: 以北京大兴机场为例. 科学技术与工程, 2025 , 25 (17) : 7405 -7416 . DOI: 10.12404/j.issn.1671-1815.2406796
Xie ZHANG, Xin-yu ZHANG, Jun ZHANG. Characteristics of Airport Traffic Flow Fluctuation Range Based on Complex Networks: Taking the Beijing Daxing International Airport as an Example[J]. Science Technology and Engineering, 2025 , 25 (17) : 7405 -7416 . DOI: 10.12404/j.issn.1671-1815.2406796
正文
收起
近年来,机场的交通流量管理变得愈加复杂而关键,尤其是在繁忙的机场,如何有效应对突发的流量波动和高峰期的挑战成为管理者们亟待解决的问题之一。机场航班延误、交通拥堵等问题,不仅直接影响旅客的出行体验,也对机场运营效率和安全性带来了挑战。空中交通流量表现为上下波动变化的非平稳、非线性运动,运用时间序列分析空中交通流量已经成为研究复杂系统演化机理和预测未来状态的重要工具[1]。时间序列是现实系统中某一观测值按时间先后顺序记录的一组数字序列,时间序列分析作为数理统计的重要分支和学术研究的热点课题,旨在从真实时间序列数据中发现统计规律以及揭示动态系统所蕴含的决策信息和演化规律[2]。王敏等[3]利用可视图方法将空中交通流时间序列转化为无标度网络,并通过拓扑分析揭示了其小世界特性、层次结构等。王超等[4]提出了基于航路网络结构的交通流识别方法,并通过递归图分析和关联维数计算揭示了不同时间尺度下流量时间序列的混沌和分形特征。围绕时间序列动力学特征,王超等[5]利用复杂网络方法分析了空中交通流时间序列的非线性特性,发现航路交通流具有混沌和分形特性,并通过网络度分布验证了这一发现。张兆宁等[6]通过建立复杂网络模型,分析航班延误在多机场网络中的传播机制,借鉴传染病模型易感者-感染者-痊愈者(susceptible-infectious-recovered,SIR)揭示延误传播的规律及重要机场的管控对延误传播的影响。
利用复杂网络理论进行时间序列分析是非线性动力学领域的关键方向之一,它为揭示动力系统的非线性特征提供了丰富的工具和观点,并在多个领域得到了广泛应用。根据不同的建网定义,将时间序列转化为复杂网络可分成3种类型[7]:第一种可视图方法直接从时间序列的数据点出发,根据数据点间的可视性或可达性规则连接节点构建可视图,反映时间序列中的局部和全局序列特征[8-9];第二种近似性网络方法通过将时间序列数据嵌入高维相空间并根据点间的距离或相似性构建节点和边,反映时间序列的动态结构[10-11];第三种转换网络方法将时间序列离散化为不同的状态,并通过分析状态之间的转移频率或概率来构建节点和边,展示状态变化的概率关系[12]。在这3种方法中可视图方法较为直观,无须人为选择参数,并且在复杂网络节点与时间序列之间存在一对一的直接对应关系,这使得由复杂网络分析得到的结果可以直接用于分析和解释原始的时间序列,因而可视图方法极其方便和高效。可视图方法可用于初步数据探索,帮助研究人员发现数据中的趋势和模式。对于构建的自适应跨越网络保留了可视图的特性,增加了对时间这一因素的考虑,量化了时间的不可逆性,注重数据间的连接关系和网络的拓扑结构,为研究空中交通流量波动的演化特征规律提供了新思路。
空中交通流量管理是在航空交通流量逼近或达到空管能力极限时的一种关键调控手段。其目的是通过适时调整,确保飞机能够最优化地流入或通过特定区域,从而提升机场和空域的运营效率及容量利用[13]。针对非线性时间序列的研究已有通过可视图[14]、有限穿透可视图[15]、去趋势波动分析[16]、多尺度多重分形分析[17]、多尺度改进排列熵[18]、改进多尺度权重排列熵[19]分析了空中交通流量时间序列的非线性波动、多尺度多重分形特性和多尺度复杂性,但仅考虑了流量波动的方向和幅值信息,未考虑机场航班流量与容量的关系以及流量涨落波动梯度等关键信息。
为了更好地理解和应对机场交通流量的波动性和高峰期的挑战,从复杂网络的角度出发,分析机场交通流量非线性的波动范围特征,探讨这些特征对机场运行的影响以及可能的解决方案。通过对网络拓扑结构、节点重要性等方面进行分析,旨在为机场交通流量管理提供新的视角和有效的决策支持,期望能够深入理解机场交通流量波动的规律性和影响因素,为机场管理决策提供科学依据,进而优化机场运行效率、提升服务质量,实现安全、高效的机场运营目标。
1 自适应跨越网络构建及特征分析
收起
1.1 自适应跨越网络
以真实交通流运行为背景,沿空中交通流时间序列横向展开。不同于可视图等众多算法,本文方法考虑了时间的不可逆性及在一定时段内前者流量大于设施容量所产生的拥堵量会累加影响在后续流量上的聚集性,会导致不同流量值在不同环境下所产生的波动影响范围不同,这个波动影响范围是受限在一定区间内的,因此构造了一种自适应跨越网络模型。根据构造原理,每个流量值根据自身情况及周围环境影响所产生的波动范围不同,会进行不同程度跨越。自适应跨越网络模型选取一定的时间间隔,节点为时间序列节点,连边定义如下:ya、yb为节点ta、tb的流量值,c为一定时段内设施容量。对于ta节点,有如下两种情况。
(1)当某个节点的交通流量小于节点容量时,只会与下一个相邻节点连边,以确保网络连边反映了低流量时的正常传递,在时间点ta和ta+1之间建立连边的条件满足关系式为
${y}_{a}\le c$
(2)当某个节点的交通流量大于节点容量时,需要逐步考虑之后的几个节点。在时间点ta和tb的连边条件是ya>c,且在ta之后逐个考虑节点${t}_{a},{t}_{a+1},{t}_{a+2},\dots,{t}_{b}$的流量和与容量和之间的关系满足关系式为
$\begin{array}{l}{y}_{a}>c,({t}_{b}-{t}_{a})c\le \stackrel{b}{\sum _{i=a}}{y}_{i}\le ({t}_{b}-{t}_{a}+1)c,\\ 　　\mathrm{且}\stackrel{\mathrm{b}-1}{\sum _{i=a}}{y}_{i}>({t}_{b}-{t}_{a})c\end{array}$
综上所述,自适应跨越网络的连边公式定义为
$\mathrm{当}{t}_{a}=\mathrm{n}\mathrm{时},\left\{\begin{array}{ll}{d}_{a}=1,& 0\le {y}_{a}\le \mathrm{c}\\ {d}_{a}={t}_{b}-{t}_{a},& {t}_{a}<{t}_{b},({t}_{b}-{t}_{a})\mathrm{c}\le \\ & \stackrel{b}{\sum _{i=a}}{y}_{i}\le ({t}_{b}-{t}_{a}+1)\mathrm{c},\\ & \mathrm{且}\stackrel{b-1}{\sum _{i=a}}{y}_{i}>({t}_{b}-{t}_{a})\mathrm{c}\end{array}\right.$
式(3)中:ta、tb为正整数且${t}_{a}\le {t}_{b}$;da为节点ta的跨越距离,da在网络中至少为1,表示为至少与下一相邻节点相连(只有邻接节点受到波动影响)与现实中情况一致,大小为所构建复杂网络的出度值,其表现为不同时间节点下节点ta的最大波动影响范围;tb为ta所能跨越到的最远节点,理解为ta~tb区间内所有节点均与ta连线。
这种逐步遍历后序节点和连边的过程体现了网络在高流量时的自适应性,通过动态调整连边规则,以反映交通流量的拥堵情况。连边的选择不仅考虑当前节点的流量,还考虑后续节点之间的流量和容量关系。只有当后续节点的流量和大于容量和时才建立连边,反之则停止连边。当流量波动较大时,容易产生高于高峰容量的节点,这些高流量节点会按照上述规则与后续多个节点产生连边。流量波动较小时,则大多数节点流量低于高峰容量,仅与下一相邻节点产生连边。这种机制使网络能够自适应地调整,以反映实际的交通流量和容量相关情况,如图1所示为网络连边的示例。
自适应跨越网络模型与经典可视图模型相比相同性质为:每个节点至少与其下一邻居节点相连;横轴和纵轴坐标尺度变化或者经过仿射变换后,连接线不变。不同性质为经典可视图为无向网络,自适应跨越网络为有向无权网络。采用自适应跨越网络算法对时间序列进行建网,能够抵抗一定的噪声,除此之外结合入度和出度的度分布可以对时间序列的不可逆性进行进一步的研究和证明。
之后根据2021年10月1日全天北京大兴机场的进离场航班真实流量数据(除去共享航班),按照时间间隔为5 min统计一天之内的起降架次(进场和离场航班架次总和),按时间顺序构建空中交通流量时间序列,共产生N=288个节点。大兴机场的高峰小时容量为62架次/h,取c为5 min时间间隔的高峰小时容量即c=62/12=5.166 7架次/5 min,航班当日流量时间序列及构建的自适应跨域网络如图2、图3所示。
1.2 自适应跨越网络的基本特征
1.2.1 点度分布特征
通过统计分析一天内空中交通流量网络拓扑结构参数,能够清晰了解到机场交通的繁忙状况,发现其结构布局存在的不足,为其今后发展提供理论支持及改善策略。此外,通过计算机场交通流量复杂网络参数能够有效地定位出整个枢纽时间段或较为重要的时间节点。对统计得到的度、入度及出度分布进行函数拟合如图4所示。
发现总度、入度及出度分布都遵循幂律分布图像特征,他们的拟合优度(Adj-R2)均在0.98以上,即证明网络是无标度网络。网络的平局度为1.19,即大多数节点的入度及出度都集中在1和2,仅有少数节点的度非常大,节点的连接度较大程度在网络的结构方面体现出重要性,对于机场来说,节点度的大小可以反映在运行过程中大多数时间节点的流量较为平稳,仅在少数高峰时段出现较大的流量波动。另外节点的出度一般会比入度稍大,入度与出度的不同可以更好地发现波动影响最强烈的节点(出度分布的最大波动范围延伸到10,入度分布的最大值不超过4),这与时间序列的不可逆性也有很大的联系,如在特定的时段内交通流量的变化会导致网络结构的不可逆变化,流量的波动范围会受到航班计划、天气、人为因素、需求等因素的影响而增加,从而导致少数节点的出度大于入度。
1.2.2 网络的同配性
在复杂网络理论中,当网络中任意节点间是否相连与它们的度值无关则称该网络不具有度相关性,即网络是中性的;否则,网络具有度相关性。同配性系数的定义就是根据节点之间的连接是否与节点的度值有关来定义的,同配性系数较高会增加航班流量波动的影响。在流量高峰时段,航班之间的连接较为集中,相互之间的流量波动更为频繁,那么相应的高峰流量时段间的度数就会相应较大,因为流量的堆积波动范围也会较远。得到的自适应跨越网络的同配性系数为0.44,表示网络中存在一定程度的同配性,在机场航班交通流量数据中,意味着在相似的时间段内,航班之间的流量连接比较密集。
1.2.3 网络的社团结构
网络的模块度是衡量网络中社团结构的一个重要指标,它描述了网络内部紧密连接的程度与节点间稀疏连接的程度之间的比率。具体来说,模块度值越接近1,表示网络内部社团结构越明显,节点在同一个社团内的连接强度越大;而模块度值越接近0,表示网络更加均匀,社团结构不太显著。得到网络的模块度为0.89,说明划分较为可靠,共划分为19个社团,如表1所示,意味着网络存在着明显的社团结构。社团结构的存在反映了空中交通流量在时空上的分布模式,每个社团对应于特定的时间段,其中机场交通流量之间存在着较为紧密的关联,而不同社团之间的航班流量关联较少。模块化分析有助于针对流量波动进行有针对性的优化和调整,有助于分析不同时段内的运行特点和规律。
2 流量波动范围节点中心性分析
收起
复杂网络中的节点不仅是信息的接收者,同时也是信息的发布者和传播者。节点的影响力在信息传播过程中发挥着巨大的作用,有影响力的节点能够推动信息的大规模扩散,快速地吸引更多的节点关注。识别机场交通流量网络中的关键枢纽节点并采取相应的调整措施,可以提高整个网络的稳健性和安全性。关键节点[20]识别的一般思路是根据某一指标对节点的影响力进行量化,并根据量化值对节点影响力进行排序[21],关键节点识别问题可看作是节点影响力度量问题。节点影响力主要是通过信息、行为等的波动体现的。因此,节点的影响力可表示为节点的波动能力,复杂网络的关键节点识别问题可看作对节点的影响力或中心性[22]的评估问题。流量的波动就是节点受到相邻质点的扰动而变化的结果,并将以流量上下起伏的形式由近及远的传播开来。
2.1 度值中心性分析
节点的度是指在网络中与节点相连接的节点的数量,在一定程度上直接反映了节点在网络中的通达性与影响力。根据自适应跨越网络的构造原理知,节点的入度、出度表示的意义分别为当前流量节点受到它前序节点的波动影响与该流量节点所处环境下所能产生的最大波动范围且与对应度数成正比关系。入度的大小可以表示当前时间节点受到前序时间节点流量波动的累积影响程度,即可能造成局部拥堵的风险,对这些节点进行监控,可以提前采取措施避免流量堆积的扩散;出度的大小表示当前时间节点对后续时间节点流量波动的影响范围,出度越大表示该时间节点对后续运行时段的影响范围广,是机场调度优化的关键节点。度的大小反映了时间节点之间的连接关系和流量波动的传递特性。在正常情况下大多数节点的出度或入度值应该等于1,在某些流量高峰时刻或由于某些特征情况时流量突然增大,使得机场超出了时段内的容量限制就会在后续时间上产生影响,从而在流量增大的时间点上节点的出度突增,使得后续节点的入度大于1,如图5所示。
机场中的航班延误指的是飞机降落在停机坪上的实际到港挡轮挡时间超过飞机计划降落时间15 min以上或者航班取消时的情况。对于某个节点来说,如果节点的度大于等于4(入度或出度度数其中一个大于等于3或都为2)就有可能对机场的正常运行造成影响。同时对于度大于等于4的节点来说,如果度数较长时间都处于大于等于4的阶段,就要注意拥堵及延误的产生。如图5所示为入度、出度的总体分布,入度及出度最小值为1,根据对机场延误的定义知,如果入度和出度都等于2(即在度数大于等于2的节点上出现􀱇)及在度大于等于3以上时,都表示当前节点是对机场有影响的重要节点。
出度较大的节点对应5 min时间序列中流量较大的值,与其流量值大小成正比关系,流量越大节点能波及的后序节点就越多。入度较大的节点表示受到前序节点的波动影响程度较强,在当前节点上产生了流量的堆积,如图6所示。
挑选出节点入度及出度中度数较大的前15个节点,从出度图[图6(b)]中可以看出,对其他节点影响较大的节点度数集中在3,出度大于等于3的节点共有11个(占整个网络的3.82%),出度上波动范围最远的节点是节点257、138和258,237尤其是节点257,在节点所处时段内机场起降架次明显增大并且持续了一段时间,使得这一段时间内的机场交通流量持续超过容量限制,由于流量的累计效应持续对后续节点产生波动影响。流量增幅最大的节点集中在257~259节点(21:20—21:35),这个时段内对后续节点的波动影响最严重,即在这个时间段内发生了拥堵并对机场正常运行产生了影响。入度大于等于3的节点共有8个(占整个网络的2.78%),入度上受到影响最严重的节点集中在260~269节点(21:35—22:25)。在这个时段之间机场内受到之前时刻如节点257等的高峰流量的波动影响还没有结束,节点流量超出了机场高峰容量所限制的范围而受到波及。从图6可以明显看出,在机场流量高峰时段结合出度、入度中心度对比分析可以得出在机场繁忙时段节点流量的波动趋势是向外辐射传播还是向内收束聚集。
2.2 聚类系数中心性分析
节点的聚类系数表示为邻居节点之间实际存在的边数与最大可能边数之比,反映一个节点的相邻节点之间相互连接的紧密情况。网络的聚类系数表示为所有节点聚类系数的平均值,反映了局部网络的稳定性和集群特性。高聚类系数区域通常对应机场运行的繁忙时段,这些区域的航班流量相互关联性高,容易形成局部波动,并且该节点被视为网络中的局部枢纽或社团中心。因此,分析聚类系数较高的节点,有助于识别潜在的局部拥堵点,并优化航班调度策略。对于有向网络的节点聚类系数Ci及整体平均聚类系数C,表达式如下。
${C}_{i}=\frac{{E}_{i}}{{k}_{i}({k}_{i}-1)}$
$C=\frac{1}{N}\stackrel{N}{\sum _{i=1}}{C}_{i}$
式中:Ei为与节点i相连的邻节点之间的的连边数;ki为节点i的总度数;N为节点总数。对于上述节点聚类系数的定义可以等价为如下几何定义,如式(6)所示。
${C}_{i}=\frac{{P}_{i}}{{Q}_{i}}=\frac{1}{{k}_{i}({k}_{i}-1)}\stackrel{N}{\sum _{j,k=1}}{a}_{ij}{a}_{ji}{a}_{ki}$
式(6)中:Pi为包含节点i三角形数目;Qi为以节点i为中心的连通三元组的数目;aijajkaki表示3个节点i,j,k之间能否构成三角形:aijajkaki=1表示三条连边能构成三角形;aijajkaki=0表示不能构成三角形。上述等价的几何定义中包含节点i的三角形结构与15 min的时间跨度相对应,即可能造成拥堵及延误的重要节点在局部邻居网络中所占的比例,在网络中节点i可能构成的所有三角形结构如图7所示,节点的相对大小表示节点的数值大小即时间先后顺序,箭头只能指向比自己大的节点表示时间的不可逆性。所以聚类系数可以在一定程度上反映那些在网络局部波动中扮演着重要角色的节点,通过找出聚类系数大于0的节点等同于发现网络中波动影响大的关键节点。
表2列出大于0的各主要节点的聚类系数。
经统计分析网络的平均聚类系数为0.101,在整个网络中表示与当前节点相连的邻居节点只有10%的邻居节点会相互连接,说明网络中大多数节点之间的局部连接比较稀疏即波动没有在长时间内持续,节点的邻居之间形成的密集子图相对较少且较为分散。较小的平均聚类系数导致时间节点的波动受限,即信息在网络中的波动范围有限,说明大部分航班的拥堵情况不太可能直接影响到其他航班,信息的波动范围局限于某些局部聚类系数较大的区域,拥堵只在某些局部范围内波动产生。在机场交通流量时间序列网络中,表明大多数时间节点与其他节点的的交叉较少,也证明了机场大多数情况都处于正常运行状态,异常流量点只可能在聚类系数较大的那一小部分中产生。
在所有节点中有95个节点(占整个网络的33%)的聚类系数不为0且都大于平均水平0.101,根据与平均聚类系数相比,这些聚类系数不为0的节点为网络中波动影响最强烈的局部中心节点。其中节点117~123(9:40—10:15)、节点135~143(11:10—11:55)、节点219~228(18:10—19:00)、节点235~244(19:30—20:20)、节点257~269(21:20—22:25)这些时间段内连续节点的聚类系数大于平均水平,表明这些节点之间形成了相对密集的连接,反映了这些时段内的交通枢纽或繁忙时段,即这些时段内存在着较为密集的航班交通流量。
2.3 特征向量中心性分析
由于构建的自适应跨越网络是沿空中交通流横向展开且保留了时间的不可逆性,所以构建出的网络结构方面表现为沿节点单向连接并只能指向比自己大的节点。在网络全局属性中如路径长度、紧密中心性、介数中心性等与网络路径相关的属性都无法表现出网络的特性而失去意义,所以不对以上几种属性进行分析讨论。
一个节点的重要性不仅取决于它的邻居节点数量(即节点的度),还取决于其邻居节点的重要性。特征向量中心性和度中心性之间存在差异,高度中心性表示节点具有大量连接而特征向量中心性并非总是高的,因为与其相连的邻居节点可能导致特征向量中心性较低,反之亦然。
高特征向量中心性的节点是航班密集时间段的关键指标,这些时间段或区域内的航班数量较多,航班之间的连接比较密集,代表机场流量中的关键时间段,是航班运行高峰期。监控这些时间点可以有效防范由于流量过载导致的连锁反应,需优先调配资源以保障运行稳定。不仅是因为这些时段本身可能面临的流量超负荷问题,更因为它们可能将问题传递给连接的其他高流量时段,如图8所示。
节点261~270的特征向量中心度排名靠前,且这些节点中的大部分节点具有较大的点度中心度,说明这些节点不仅具有较大的波动影响力且与网络中的重要的核心节点相关联,受到他们直接或间接的波动影响。其中部分节点的特征向量度值较大但点度值较小,如节点264、269和270,这说明他们虽然与网络中波动强烈的节点相连但其波动影响能力较弱,是网络中较为稳定的重要核心节点。
2.4 core-shell中心性分析
k-core算法通常用来找出一个图中符合指定k核心度的子图,该子图在图中承担着核心的地位,核心度越高,子图越小,该子图对应的核心度也越大。无论子图外部有多少个链接,子图内每个节点至少与其他节点有k个连接。k核可以识别密集连接的区域,并且为了包含在k核心中,一个节点必须至少有k条连接到该区域中的其他节点。
k-shell分解算法是一种粗粒化的节点重要性分类方法,可用于识别网络中的关键节点和网络的稳定性。选取节点的出度作为k-shell分解的依据对网络进行划分,通过不断地去除出度数最小的节点和与其相连的边来进行网络的分层,直到网络中所有节点都被分到某个k-shell中或没有节点剩余为止。网络内层较大k-shell节点在网络中具有更高的波动影响力,而外层较小的节点只对网络的结构稳定性起到重要作用。
k-core侧重于识别网络中的核心部分,着眼于节点的度和连接密度,用于寻找最具影响力或者功能核心的节点集合。k-shell侧重于节点的层次结构,将网络中的节点按照连接度进行分层,用于识别网络中的关键节点和层次结构。在5 min时间粒度的自适应跨越网络中,如果节点的k-core大于等于3时,说明节点的波动影响范围就会在15 min以上,高核心节点通常出现在高峰运行时段,对网络的整体运行稳定性起关键作用,这些节点的流量波动直接影响到机场的运行效率和安全性。识别4核及3核节点等价于找到了网络中强波动的节点,其中3核节点中包括4核的节点,这些节点对网络的稳定性和连通性至关重要。确定4核和3核节点所代表的航班或航线,可以有针对性地进行航班调度优化。例如,对4核节点的延误进行及时干预和管理,可以减少航班延误对整个航班网络的波动影响。4核和3核节点的识别也为应急响应提供了依据。在突发情况下,可以优先处理这些波动影响范围最广的核心节点,以最大限度地减少对整个航班网络的波动影响。4核和3核的分析结果对于理解网络结构的关键节点及评估网络稳定性具有重要意义。
选出网络中所有的4核及3核节点及各个节点的k-shell值并标注在节点,如图9所示,在这些紧密连接的核心中大部分节点的流量都较高且与多个时间点之间密切相关。这些时间跨度大于15 min的节点表明一旦这些节点出现问题,其影响就会迅速传递至核心中的其他节点造成更大范围的波动,这些高核心时间节点应成为资源配置(如安检、值机柜台、登机口分配等)和员工调度的焦点区域。
结合两种算法的结果,对每个节点的k-shell和k-core分别进行归一化并对两种值进行加权平均处理,找出既在网络中具有核心地位又在层次结构上处于高层次的节点,如图10所示,这些节点是网络中波动范围最大的关键节点和波动传递的关键媒介。
根据对core-shell度值的中心性分析,节点的core-shell中心度值整体出现断层现象,说明通过特征向量度值可以明显区分网络中那些波动最强烈的节点且波动能力强弱参差不齐。节点257、258拥有最大的度,处于网络中的最核心位置,其次是138、259节点,之后节点的度值差距逐渐缩小且呈阶梯式下降,根据度值大小可以较好地区分节点的重要程度,明确波动范围最强烈的时间节点。
2.5 综合中心性分析
上述表现网络结构的指标特点各异,反映出的网络特征也各有侧重。各网络拓扑指标多是从网络的某一方面来对网络进行刻画,如果网络的结构在某一方面表现显著就会有较好的效果。因此,利用独立性权系数法对各种中心度指标(出度中心度、入度中心度、聚类系数中心度、特征向量中心度、core-shell中心度)进行综合中心度[23]的计算来找到网络中波动能力最强的核心节点。独立性权系数法用于评估各指标之间的独立性程度和相对重要性,通过计算指标之间的共线性关系来确定权重,共线性越强指标之间的相互依赖性越高,其权重就越低。即若该指标与其他指标的复相关系数R越大,该指标的权重越小,最后利用归一化的权重对每个节点的各指标进行加权求和取R的倒数得出综合中心度的大小,其中复相关系数如式(7)所示。
$\mathrm{R}=\frac{\sum ({y}_{i}-\overline{y}\left)\right({\hat{\mathrm{y}}}_{\mathrm{i}}-\overline{y})}{\sqrt{\sum ({y}_{i}{-\overline{y})}^{2}\sum ({\hat{\mathrm{y}}}_{\mathrm{i}}{-\overline{y})}^{2}}}$
式(7)中:复相关系数R的取值范围为[0,1];yi为各节点的综合中心度,i的范围为[1,N],N为时间序列长度;$\overline{y}$为样本均值;${\hat{\mathrm{y}}}_{\mathrm{i}}$为回归估计值。
经过对各节点中心度的整合得出如图11所示的各节点波动强度排名,根据综合中心度的分析结果可以看出,在一天内的机场交通流量节点波动范围影响程度出现几段阶梯式的下降,节点综合中心度值在0.6~2.4的前70个节点视为强波动节点,而连续强波动节点处于网络中骨干枢纽的重要地位,其中节点119~123(9:50—10:15)、节点140~143(11:35—11:55)、节点239~242(19:50—20:10)、节点257~269(21:20—22:25)都是网络中波动能力突出的核心时间节点。可以看出上述得到的波动范围大的时段都包含在某一的社团中,说明社团内的波动会影响同一社团内的其他节点,而不会对其他社团内的节点产生明显的影响,也从侧面强调了综合中心度有效地刻画了网络中的强波动核心节点。其次波动影响较强的节点分布在0.44~0.6附近,波动影响能力较弱的分布在0.2~0.43的剩余节点中,大部分正常的节点波动影响范围分布在0.2~0.43。一天之内的流量波动分布在不同的时段且呈现出不同的波动强度,根据综合中心度值的大小可以明显地判断出一天之中的强波动节点及时间点。这种方法可以帮助决策者在机场产生特殊情况时可以鉴别波动影响范围最大的时间点及理解哪些时间点对机场总体的影响程度最大,并指导策略和方案的制定。
3 结论
收起
得到的主要研究结论如下。
(1)构建的自适应跨越网络表现出节点度分布符合幂律分布,具有无标度性,网络是度正相关的,并且显示出明显的社团结构。其中网络中少数节点具有较高的连接度,而多数节点的连接度较低,这种结构有助于理解机场交通流量的分布和影响范围。
(2)在网络节点中心性方面,节点257~269等节点的综合中心度值较高,其点度、聚类系数、特征向量中心度和core-shell中心度的排名均处于前列,这些节点属于网络中的骨干枢纽,其对应的时间段是机场流量的高峰期,易造成大范围的流量波动影响。网络中其他强波动节点虽然综合度值排名靠前,但各项中心度指标差异较大,未能形成稳定的骨干结构。
(3)对自适应跨越网络的出度中心度、入度中心度、聚类系数中心度、特征向量中心度及core-shell中心度进行综合分析,发现网络综合中心度值呈阶梯式下降分布,具有明显的阶段性。这种分布特征有效刻画出网络中波动影响范围最强烈的核心节点,提供了识别机场流量波动的关键信息。
基金
收起
  • 国家自然科学基金联合基金(U2133210)
  • 中央高校基本科研业务费专项资金(312202YY02)
文献
收起
参考文献 引证文献
排序方式：
[1]
韩敏, 任伟杰, 李柏松, 等. 混沌时间序列分析与预测研究综述[J]. 信息与控制, 2020, 49(1): 24-35.
Han Min, Ren Weijie, Li Baisong, et al. Survey of chaotic time series analysis and prediction[J]. Information and Control, 2020, 49(1): 24-35.
[2]
李海林, 王杰, 周文浩, 等. 时间序列复杂网络分析中的可视图方法研究综述[J]. 电子学报, 2023, 51(9): 2598-2622.
Li Hailin, Wang Jie, Zhou Wenhao, et al. A review of visibility graph methods research in time series complex network analysis[J]. Acta Electronica Sinica, 2023, 51(9): 2598-2622.
[3]
王敏, 朱明. 基于复杂网络理论的空中交通流时间序列分析[J]. 航空计算技术, 2020, 50(5): 61-65.
Wang Min, Zhu Ming. Time series analysis of air traffic flow based on complex network theory[J]. Aeronautical Computing Technology, 2020, 50(5): 61-65.
[4]
王超, 郑旭芳, 王蕾. 交汇航路空中交通流的非线性特征研究[J]. 西南交通大学学报, 2017, 52(1): 171-178.
Wang Chao, Zheng Xufang, Wang Lei. Research on nonlinear characteristics of air traffic flows on converging air routes[J]. Journal of Southwest Jiaotong University, 2017, 52(1): 171-178.
[5]
王超, 朱明. 基于复杂网络表征ATF时间序列动力学特性[J]. 计算机仿真, 2018, 35(6): 81-85.
Wang Chao, Zhu Ming. Representation of air traffic flow time series dynamic characteristics based on complex network[J]. Computer Simulation, 2018, 35(6): 81-85.
[6]
张兆宁, 孟凡淑. 基于复杂网络的多机场航班延误传播分析[J]. 科学技术与工程, 2024, 24(18): 7913-7920.
Zhang Zhaoning, Meng Fanshu. Complex network-based analysis of multi-airport flight delay propagation[J]. Science Technology and Engineering, 2024, 24(18): 7913-7920.
[7]
Zou Y, Donner R V, Marwan N, et al. Complex network approaches to nonlinear time series analysis[J]. Physics Reports, 2019, 787: 1-97.
[8]
Lacasa L, Luque B, Ballesteros F, et al. From time series to complex networks: the visibility graph[J]. Proceedings of the National Academy of Sciences, 2008, 105(13): 4972-4975.
[9]
Donner R V, Donges J F. Visibility graph analysis of geophysical time series: potentials and possible pitfalls[J]. Acta Geophys, 2012, 60: 589-623.
[10]
Marwan N, Donges J F, Zou Y, et al. Complex network approach for recurrence analysis of time series[J]. Physics Letters A, 2009, 373(46): 4246-4254.
[11]
Donner R V, Small M, Donges J F, et al. Recurrence-based time series analysis by means of complex network methods[J]. International Journal of Bifurcation and Chaos, 2011, 21: 1019-1046.
[12]
Nicolis G, Cantu A G, Nicolis C. Dynamical aspects of interaction networks[J]. International Journal of Bifurcation and Chaos, 2005, 15: 3467-3480.
[13]
中华人民共和国交通运输部. 民用航空空中交通管理规则[S]. 北京: 中华人民共和国交通运输部, 2017.
Ministry of transport of the People's Republic of China. Civil aviation air traffic management regulations[S]. Beijing: Ministry of Transport of the People's Republic of China, 2017.
[14]
Liu H Z, Zhang X C, Zhang X. Exploring dynamic evolution and fluctuation characteristics of air traffic flow volume time series: a single waypoint case[J]. Physica A: Statistical Mechanics and its Applications, 2018, 503: 560-571.
[15]
张勰, 肖恩媛, 刘宏志, 等. 基于有限穿越可视图的进场航班流量波动特性研究[J]. 交通运输系统工程与信息, 2022, 22(6): 244-257.
Zhang Xie, Xiao Enyuan, Liu Hongzhi, et al. Fluctuation characteristics of arrival flight flow based on limited penetrable visibility graph[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(6): 244-257.
[16]
Zhang X, Liu H Z, Zhao Y, et al. Multifractal detrended fluctuation analysis on air traffic flow time series: a single airport case[J]. Physica A: Statistical Mechanics and Its Applications, 2019, 531: 121790.
[17]
Liu H Z, Zhang X C, Zhang X. Multiscale multifractal analysis on air traffic flow time series: a single airport departure flight case[J]. Physica A: Statistical Mechanics and Its Applications, 2020, 545: 123585.
[18]
Liu H Z, Zhang X C, Zhang X. Multiscale complexity analysis on airport air traffic flow volume time series[J]. Physica A: Statistical Mechanics and Its Applications, 2020, 548: 124485.
[19]
Liu H Z, Zhang X, Hu H, et al. Exploring the impact of flow values on multiscale complexity quantification of airport flight flow fluctuations[J]. Chaos, Solitons & Fractals, 2022, 165: 112795.
[20]
姜敏勤, 石小晶, 杨钰, 等. 基于节点重要度动态评估的复杂网络级联失效分析[J]. 科学技术与工程, 2023, 23(31): 13482-13491.
Jiang Minqin, Shi Xiaojing, Yang Yu, et al. Complex network cascade failure analysis based on dynamic evaluation of node importance[J]. Science Technology and Engineering, 2023, 23(31): 13482-13491.
[21]
徐开俊, 肖成坤, 杨泳, 等. 基于复杂网络理论的中国城市航空网络有向加权分析[J]. 科学技术与工程, 2021, 21(36): 15669-15673.
Xu Kaijun, Xiao Chengkun, Yang Yong, et al. Directed weighted analysis of domestic urban aviation network based on complex network theory[J]. Science Technology and Engineering, 2021, 21(36): 15669-15673.
[22]
张瑞, 朱春彦, 王琼, 等. 基于复杂网络的中国四大机场群多极航线网络结构特征分析[J]. 科学技术与工程, 2023, 23(18): 8002-8010.
Zhang Rui, Zhu Chunyan, Wang Qiong, et al. Analysis on the characteristics of airline network in China's four major multiple-airport systems based on complex network[J]. Science Technology and Engineering, 2023, 23(18): 8002-8010.
[23]
李振福, 王紫荆. 不同运输方式下大北极综合交通运输网络特性研究[J]. 世界地理研究, 2023, 32(7): 24-35.
Li Zhenfu, Wang Zijing. Research on the characteristics of Pan Arctic comprehensive transportation network under different transportation mode[J]. World Regional Studies, 2023, 32(7): 24-35.
2025年第25卷第17期
PDF下载
119
54
引用本文
BibTeX
文章信息
doi: 10.12404/j.issn.1671-1815.2406796
  • 接收时间：2024-09-10
  • 首发时间：2025-12-15
  • 出版时间：2025-06-18
补充材料
相关文章
文章信息
作者
出版历史
  • 收稿日期：2024-09-10
基金
国家自然科学基金联合基金(U2133210)
中央高校基本科研业务费专项资金(312202YY02)
作者信息
    1 中国民航大学空中交通管理学院, 天津 300300
    2 山东省机场集团临沂国际机场航务管理部, 临沂 276037
参考文献
分享链接
https://castjournals.cast.org.cn/joweb/kxjsygc/CN/10.12404/j.issn.1671-1815.2406796
分享至
全文二维码

扫描看全文

引用本文
BibTeX
本文的引用情况
2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
相关链接
论文
最新文章
热读文章
热点专题
内参
蓝皮书
产业发展报告
传播力报告
期刊分级目录
资讯
学术新闻
行业新闻
学术会议
行业会议
关于
关于我们
联系我们
北京市海淀区学院南路86号
100081
010-62199257
qkjq@cast.org.cn

中国科学技术协会版权所有 京ICP 备10216604号-4 海淀分局备案 1101084647
科技导报社主办 中国科协信息中心技术支持