A Model for Airport Congestion Propagation in Chinese Airline Network

2019 ◽  
Author(s):  
Jinglei Huang ◽  
Qiucheng Xu ◽  
Yongjie Yan
Keyword(s):  
Airline Network ◽  
Airport Congestion

scholarly journals Modeling airport congestion contagion by heterogeneous SIS epidemic spreading on airline networks

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245043
Author(s):  
Alberto Ceria ◽  
Klemens Köstler ◽  
Rommy Gobardhan ◽  
Huijuan Wang
Keyword(s):  
Recovery Rate ◽  
Homogeneous Model ◽  
Stable State ◽  
Spreading Process ◽  
Sis Model ◽  
Heterogeneous Model ◽  
The Us ◽  
Airline Networks ◽  
Airline Network ◽  
Airport Congestion

In this work, we explore the possibility of using a heterogeneous Susceptible- Infected-Susceptible SIS spreading process on an airline network to model airport congestion contagion with the objective to reproduce airport vulnerability. We derive the vulnerability of each airport from the US Airport Network data as the congestion probability of each airport. In order to capture diverse flight features between airports, e.g. frequency and duration, we construct three types of airline networks. The infection rate of each link in the SIS spreading process is proportional to its corresponding weight in the underlying airline network constructed. The recovery rate of each node is also heterogeneous, dependent on its node strength in the underlying airline network, which is the total weight of the links incident to the node. Such heterogeneous recovery rate is motivated by the fact that large airports may recover fast from congestion due to their well-equipped infrastructures. The nodal infection probability in the meta-stable state is used as a prediction of the vulnerability of the corresponding airport. We illustrate that our model could reproduce the distribution of nodal vulnerability and rank the airports in vulnerability evidently better than the SIS model whose recovery rate is homogeneous. The vulnerability is the largest at airports whose strength in the airline network is neither too large nor too small. This phenomenon can be captured by our heterogeneous model, but not the homogeneous model where a node with a larger strength has a higher infection probability. This explains partially the out-performance of the heterogeneous model. This proposed congestion contagion model may shed lights on the development of strategies to identify vulnerable airports and to mitigate global congestion by e.g. congestion reduction at selected airports.

scholarly journals Study on Structural Characteristics of China’s Passenger Airline Network Based on Network Motifs Analysis

2019 ◽  
Vol 11 (9) ◽  
pp. 2484 ◽  
Author(s):  
Ying Jin ◽  
Ye Wei ◽  
Chunliang Xiu ◽  
Wei Song ◽  
Kaixian Yang
Keyword(s):  
Airline Industry ◽  
Structural Characteristics ◽  
Building Blocks ◽  
Development Stage ◽  
Network Motifs ◽  
Characteristic Analysis ◽  
Airline Networks ◽  
Airline Network ◽  
Industry Sustainability ◽  
Advanced Development

The air passenger transport network system is an important agent of social and economic connections between cities. Studying on the airline network structure and providing optimization strategies can improve the airline industry sustainability evolution. As basic building blocks of broad networks, the concept of network motifs is cited in this paper to apply to the structural characteristic analysis of the passenger airline network. The ENUMERATE SUBGRAPHS (G, k) algorithm is used to identify the motifs and anti-motifs of the passenger airline network in China. A total of 37 airline companies are subjected to motif identification and exploring the structural and functional characteristics of the airline networks corresponding to different motifs. These 37 airline companies are classified according to the motif concentration curves into three development stages, which include mono-centric divergence companies at the low-level development stage, transitional companies at the intermediate development stage, and multi-centric and hierarchical companies at the advanced development stage. Finally, we found that adjusting the number of proper network motifs is useful to optimize the overall structure of airline networks, which is profitable for air transport sustainable development.

Research Paper Influence Measurement and Applications: A Machine-Learning-Based Approach

2014 ◽  
Vol 1049-1050 ◽  
pp. 2073-2078
Author(s):  
San Shan Du ◽  
Yue Chun Wu
Keyword(s):  
Machine Learning ◽  
Graph Theory ◽  
Academic Research ◽  
Meaningful Work ◽  
Citation Network ◽  
Citation Networks ◽  
Research Publication ◽  
American Airline ◽  
Airline Network ◽  
Influence Measurement

Measuring the influence of academic research publication is an meaningful work in academe. In this paper, the co-author and the citation networks are built to calculate the influence of a researcher and a paper in the way of networks separately with the discussion of further applications. At the beginning, the co-author network is built to determine the influence of co-authors. Then, based on the citations among the papers in the database, we build up the citation network with the help of graph theory. Thirdly, the method is implemented with the application of American Airline network analysis. As the final, the analysis of strengths and weaknesses is conducted.

scholarly journals Attractiveness-Based Airline Network Models with Embedded Spill and Recapture

2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Desmond Di Wang ◽  
Diego Klabjan ◽  
Sergey Shebalov
Keyword(s):  
Network Models ◽  
Airline Network
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