Journal
CHAOS
Volume 31, Issue 11, Pages -Publisher
AIP Publishing
DOI: 10.1063/5.0056864
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Funding
- Key Program of Shanghai Soft Science [21692192900]
- National Natural Science Foundation of China (NNSFC) [42001114]
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This study explores the evolutionary pattern of the world container shipping network (WCSN) and reveals that its hierarchy largely depends on trade patterns and demonstrates certain geographic characteristics. The KS-LRW index performs best in evaluating network performance, and future simulation results show that predicting potential edges can significantly enhance network connectivity and efficiency.
Although the world container shipping network (WCSN) has gradually been shaped with ever-increasing complexity in link evolution over the last decades, its evolving mechanism remains to be unveiled. This motivates us to explore the evolutionary pattern of the WCSN, which can be achieved by advancing the existing link prediction models. Using the k-shell decomposition method, the network hierarchy can be decomposed and evaluated by four indices which are KS-Salton, KS-AA, KS-RA, and KS-LRW. The results show that the network hierarchy depends largely on trade patterns and demonstrates certain geographic characteristics. Meanwhile, the KS-LRW index performs best and, therefore, is further simulated for the future WCSN by predicting its top 1677 potential edges, which significantly enhances the overall network connectivity and efficiency. These findings create profound implications for shipping companies to strategically reduce the trail cost for new lines by analyzing the network data.
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