Recent Progress about Flight Delay under Complex Network
Flight delay is one of the most challenging threats to operation of air transportation network system. Complex network was introduced into research studies on flight delays due to its low complexity, high flexibility in model building, and accurate explanation about real world. We surveyed recent pr...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/5513093 |
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| author | Tang Zhixing Huang Shan Han Songchen |
| author_facet | Tang Zhixing Huang Shan Han Songchen |
| author_sort | Tang Zhixing |
| collection | DOAJ |
| description | Flight delay is one of the most challenging threats to operation of air transportation network system. Complex network was introduced into research studies on flight delays due to its low complexity, high flexibility in model building, and accurate explanation about real world. We surveyed recent progress about flight delay which makes extensive use of complex network theory in this paper. We scanned analyses on static network and temporal evolution, together with identification about topologically important nodes/edges. And, we made a clarification about relations among robustness, vulnerability, and resilience in air transportation networks. Then, we investigated studies on causal relations, propagation modellings, and best spreaders identifications in flight delay. Ultimately, future improvements are summarized in fourfold. (1) Under Complex Network, flight operation relevant subsystems or sublayers are discarded by the majority of available network models. Hierarchical modelling approaches may be able to improve this and provide more capable network models for flight delay. (2) Traffic information is the key to narrow the gap between topology and functionality in current situations. Flight schedule and flight plan could be employed to detect flight delay causalities and model flight delay propagations more accurately. Real flight data may be utilized to validate and revise the detection and prediction models. (3) It is of great importance to explore how to predict flight delay propagations and identify best spreaders at a low cost of calculation complexity. This may be achieved by analyzing flight delay in frequency domain instead of time domain. (4) Summation of most critical nodes/edges may not be the most crucial group to network resilience or flight delay propagations. Effective algorithm for most influential sequence is to be developed. |
| format | Article |
| id | doaj-art-e34000a19bbc45389b1667940fc1ae61 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-e34000a19bbc45389b1667940fc1ae612025-02-03T01:28:43ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/55130935513093Recent Progress about Flight Delay under Complex NetworkTang Zhixing0Huang Shan1Han Songchen2College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan, ChinaLibrary, Civil Aviation Flight University of China, Guanghan, ChinaSchool of Aeronautics and Astronautics, Sichuan University, Chengdu, ChinaFlight delay is one of the most challenging threats to operation of air transportation network system. Complex network was introduced into research studies on flight delays due to its low complexity, high flexibility in model building, and accurate explanation about real world. We surveyed recent progress about flight delay which makes extensive use of complex network theory in this paper. We scanned analyses on static network and temporal evolution, together with identification about topologically important nodes/edges. And, we made a clarification about relations among robustness, vulnerability, and resilience in air transportation networks. Then, we investigated studies on causal relations, propagation modellings, and best spreaders identifications in flight delay. Ultimately, future improvements are summarized in fourfold. (1) Under Complex Network, flight operation relevant subsystems or sublayers are discarded by the majority of available network models. Hierarchical modelling approaches may be able to improve this and provide more capable network models for flight delay. (2) Traffic information is the key to narrow the gap between topology and functionality in current situations. Flight schedule and flight plan could be employed to detect flight delay causalities and model flight delay propagations more accurately. Real flight data may be utilized to validate and revise the detection and prediction models. (3) It is of great importance to explore how to predict flight delay propagations and identify best spreaders at a low cost of calculation complexity. This may be achieved by analyzing flight delay in frequency domain instead of time domain. (4) Summation of most critical nodes/edges may not be the most crucial group to network resilience or flight delay propagations. Effective algorithm for most influential sequence is to be developed.http://dx.doi.org/10.1155/2021/5513093 |
| spellingShingle | Tang Zhixing Huang Shan Han Songchen Recent Progress about Flight Delay under Complex Network Complexity |
| title | Recent Progress about Flight Delay under Complex Network |
| title_full | Recent Progress about Flight Delay under Complex Network |
| title_fullStr | Recent Progress about Flight Delay under Complex Network |
| title_full_unstemmed | Recent Progress about Flight Delay under Complex Network |
| title_short | Recent Progress about Flight Delay under Complex Network |
| title_sort | recent progress about flight delay under complex network |
| url | http://dx.doi.org/10.1155/2021/5513093 |
| work_keys_str_mv | AT tangzhixing recentprogressaboutflightdelayundercomplexnetwork AT huangshan recentprogressaboutflightdelayundercomplexnetwork AT hansongchen recentprogressaboutflightdelayundercomplexnetwork |