Exploring Delay Propagation Causality in Various Airport Networks with Attention-Weighted Recurrent Graph Convolution Method
Exploring Delay Propagation Causality in Various Airport Networks with Attention-Weighted Recurrent Graph Convolution Method
复制标题
DOI：
10.3390/aerospace10050453
复制
发表时间：
2023-05
期刊：
影响因子：
2.6
通讯作者：
Jiawei Kang;Shangwen Yang;Xiaoxuan Shan;J. Bao;Zhao Yang
中科院分区：
文献类型：
--
作者：
Jiawei Kang;Shangwen Yang;Xiaoxuan Shan;J. Bao;Zhao Yang
探索机场之间的延误因果关系，并比较不同机场网络的延误传播模式，是更好地理解延误传播机制，并提供有效的延误缓解策略的关键。提出了一种新的基于注意力的递归图卷积神经网络来识别中国三个不同机场网络中机场之间的隐藏延误因果关系。选取的三个机场网络在平均强度、模块度和特征向量中心度等拓扑特征上表现出很大的异质性。建模结果表明，三个机场网络的延误因果网络识别的复杂性，延误传播距离和效率有很大的差异。此外，每个机场的延误状态分为三个层次，并探讨了三个网络的延误状态转换。结果表明，华北管制区延误状态的转换呈现出明显的双向转换形式，主要在大度数机场和小度数机场之间传播，而部分枢纽机场的严重延误在其他两个网络中所占比例较大。研究结果可以更好地揭示航班延误在机场间的传播机理，帮助机场运营商制定有效的缓解航班延误的策略，提高机场运营效率。
Exploring the delay causality between airports and comparing the delay propagation patterns across different airport networks is critical to better understand delay propagation mechanisms and provide effective delay mitigation strategies. A novel attention-based recurrent graph convolutional neural network is proposed to identify the hidden delay causality relationship among airports in three different airport networks of China. The selected three airport networks show great heterogeneities in topological characteristics, such as average intensity, modularity and eigenvector centrality. The modeling results indicate that the identified delay causality networks of three airport networks are greatly varied in terms of complexity, delay propagation distance and efficiency. Moreover, the delay state of each airport is categorized into three levels, and the delay state transition of the three networks is explored. The results indicate that delay state transition in the North China Control Area exhibits an obvious bidirectional transition form that mainly propagates between the large-degree airports and small-degree airports, while severe delays of some hub airports account for a relatively large proportion in the other two networks. The results of this study could better reveal the delay propagation mechanism among airports and help airport operators develop effective strategies to alleviate flight delays and improve airport operation efficiency.