基于多层网络的区域间交通网络分析综述

IF 5.3 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Jiaqi Li, Zhenfu Li, Xinli Qi
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引用次数: 0

摘要

区域间交通网络对区域人口流动、贸易流动和经济发展具有重要影响。与单层网络相比,多层网络理论可以帮助itn获取更详细的信息,应用于交通规划、设计和管理。尽管人们对使用多层网络分析来研究itn越来越感兴趣,但记录和更好地理解这一领域的尝试在很大程度上仍然是难以捉摸的。为了填补这一空白,本文对基于多层网络的itn分析进行了全面的文献计量评估。本文系统评述了基于多层网络理论的ITNs的结构、特点和功能三个方面的研究。通过分析,基于多层网络的itn研究正从航空网络向其他itn扩展,从静态网络向动态网络发展。未来,在层间关系的建立、复合ITNs的发展、动态网络风险传播的有效管理以及系统鲁棒性的增强等方面有望取得进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A review of multilayer networks-based interregional transportation networks analysis
The interregional transportation networks (ITNs) have a significant impact on regional population movement, trade flow and economic development. Compared to single-layer networks, multilayer networks theory can help ITNs to capture more detailed information applied to transportation plan, design and management. Despite the growing interest in studying ITNs using multilayer network analysis, attempts to document and better understand this area have largely remained elusive. To fill the gap, this article provides a comprehensive bibliometric assessment of multilayer networks-based ITNs analysis. Three research aspects, including the construction, characteristics, and functions of ITNs analysis based on multilayer networks theory has been systematically reviewed. Through analysis, research on multilayer networks-based ITNs are expanding from aviation networks to other ITNs and evolving from static to dynamic networks. In the future, advancements are expected in the establishment of interlayer relationships, the development of composite ITNs, effective management of dynamic network risk propagation, and enhancement of system robustness.
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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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