跳到主要导航 跳到搜索 跳到主要内容

Network modelling and resilience analysis of air transportation: A data-driven, open-source approach

科研成果: 书/报告/会议事项章节 › 章节 › 同行评审

摘要

The effectiveness and resilience of air transportation, as a complex socio-technical system, can be adequately analyzed using tools of Network Science, a recently developed academic field that studies components and interactions among them. Network Science, together with another recently emerged field, Data Science, leverages the scalable and realistic analysis of air transportation. The goal of this chapter is to design, implement, and disseminate an open-source framework for the analysis of air transportation networks, their performance, and their resilience. First, the chapter derives a framework for modeling air transportation networks based on freely available datasets. Second, we provide an overview on how to estimate the resilience of such a complex system, with methods developed in the Network Science community. Third, we perform experiments on global air transportation, reporting on critical roles of its elements. Our framework, implemented in Python, makes it easy for other transportation researchers to get started in the area of air transportation network resilience, by having a gold standard as reference. Moreover, since our framework and its underlying data are freely available, we hope that it can push the state-of-the-art in air transportation network resilience analysis.

源语言英语
主期刊名Data-Driven Solutions to Transportation Problems
出版商Elsevier
页227-245
页数19
ISBN(电子版)9780128170267
ISBN(印刷版)9780128170274
DOI
出版状态已出版 - 1 1月 2018

学术指纹

探究 'Network modelling and resilience analysis of air transportation: A data-driven, open-source approach' 的科研主题。它们共同构成独一无二的学术指纹。

引用此