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Structural and spectral properties of generative models for synthetic multilayer air transportation networks
To understand airline transportation networks (ATN) systems we can effectively represent them as multilayer networks, where layers capture different airline companies, the nodes correspond to the airports and the edges to the routes between the airports. We focus our study on the importance of lever...
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Published in: | PloS one 2021-10, Vol.16 (10), p.e0258666-e0258666 |
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description | To understand airline transportation networks (ATN) systems we can effectively represent them as multilayer networks, where layers capture different airline companies, the nodes correspond to the airports and the edges to the routes between the airports. We focus our study on the importance of leveraging synthetic generative multilayer models to support the analysis of meaningful patterns in these routes, capturing an ATN's evolution with an emphasis on measuring its resilience to random or targeted attacks and considering deliberate locations of airports. By resorting to the European ATN and the United States ATN as exemplary references, in this work, we provide a systematic analysis of major existing synthetic generation models for ATNs, specifically ANGEL, STARGEN and BINBALL. Besides a thorough study of the topological aspects of the ATNs created by the three models, our major contribution lays on an unprecedented investigation of their spectral characteristics based on Random Matrix Theory and on their resilience analysis based on both site and bond percolation approaches. Results have shown that ANGEL outperforms STARGEN and BINBALL to better capture the complexity of real-world ATNs by featuring the unique properties of building a multiplex ATN layer by layer and of replicating layers with point-to-point structures alongside hub-spoke formations. |
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Results have shown that ANGEL outperforms STARGEN and BINBALL to better capture the complexity of real-world ATNs by featuring the unique properties of building a multiplex ATN layer by layer and of replicating layers with point-to-point structures alongside hub-spoke formations.</description><subject>Aeronautics</subject><subject>Air transportation</subject><subject>Air transportation industry</subject><subject>Aircraft</subject><subject>Aircraft - statistics & numerical data</subject><subject>Airlines</subject><subject>Airports</subject><subject>Algorithms</subject><subject>Humans</subject><subject>Matrix theory</subject><subject>Methods</subject><subject>Modelling</subject><subject>Models, Theoretical</subject><subject>Multilayers</subject><subject>Percolation</subject><subject>Properties</subject><subject>Resilience</subject><subject>Social networks</subject><subject>Statistical models</subject><subject>System effectiveness</subject><subject>Transportation - methods</subject><subject>Transportation networks</subject><subject>Travel - 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subjects | Aeronautics Air transportation Air transportation industry Aircraft Aircraft - statistics & numerical data Airlines Airports Algorithms Humans Matrix theory Methods Modelling Models, Theoretical Multilayers Percolation Properties Resilience Social networks Statistical models System effectiveness Transportation - methods Transportation networks Travel - statistics & numerical data |
title | Structural and spectral properties of generative models for synthetic multilayer air transportation networks |
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