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圈比作为一种基于圈结构的量化指标，已在无权无向网络中展现出其在识别关键节点方面的显著优势。传统的圈比未能充分考虑边权信息对网络结构的影响，限制了其在更广泛网络分析中的应用。为了解决这一问题，本文提出了一种加权网络中新的网络分析指标——加权圈比，旨在提升识别加权网络中关键节点的准确性。通过对示例网络的分析，验证了加权圈比的可行性；进一步的实验在多个真实世界的网络中表明，加权圈比不仅与现有的基准指标存在显著差异，而且在评估网络连通性及早期传播覆盖范围方面，总体表现优于包括传统圈比在内的其他基准指标。这些发现强调了加权圈比在网络分析中的潜在价值，尤其是在处理加权网络时的有效性.In the face of surging air transportation demands and increasingly intense flight conflict risks, effectively managing flight conflicts and accurately identifying key conflicting aircraft have become critically important. This paper presents a novel method for identifying critical nodes in flight conflict networks by integrating complex network theory with a weighted cycle ratio (WCR). By modeling aircraft as nodes and conflict relationships as edges, we construct a flight conflict network where the urgency of conflicts is reflected in edge weights. We extend the traditional cycle ratio (CR) concept to propose the WCR, which accounts for both the topological structure of the network and the urgency of conflicts. Furthermore, we combine the WCR with node strength (NS) to form an adjustable mixed indicator (MI), which adaptively balances the importance of nodes based on their involvement in cyclic conflict structures and their individual conflict intensity. Through extensive simulations, including node deletion experiments and network robustness analyses, we demonstrate that our method can precisely pinpoint critical nodes in flight conflict networks. The results indicate that regulating these critical nodes can significantly reduce network complexity and conflict risks. Importantly, our method's effectiveness grows with the complexity of the flight conflict network, making it especially suitable for scenarios with high aircraft densities and intricate conflict patterns. Overall, this study not only advances the theoretical understanding of complex network analysis in aviation but also offers a practical tool for enhancing air traffic control efficiency and safety, ultimately contributing to greener and more sustainable air transportation.
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Keywords:
- Complex network /
- Cycle ratio /
- Weighted cycle ratio /
- vital node
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