Maritime Traffic Knowledge Discovery via Knowledge Graph Theory DOI Creative Commons
Shibo Li, Jiajun Xu, Xinqiang Chen

et al.

Journal of Marine Science and Engineering, Journal Year: 2024, Volume and Issue: 12(12), P. 2333 - 2333

Published: Dec. 19, 2024

Intelligent ships are a key focus for the future development of maritime transportation, relying on efficient decision-making and autonomous control within complex environments. To enhance perception, prediction, capabilities these ships, present study proposes novel approach constructing time-series knowledge graph, utilizing real-time Automatic Identification System (AIS) data analyzed via sliding window technique. By integrating advanced technologies such as extraction, representation learning, semantic fusion, both static dynamic navigational systematically unified graph. The specifically targets extraction modeling critical events, including variations in ship speed, course changes, vessel encounters, port entries exits. evaluate urgency mathematical algorithms applied to Distance Closest Point Approach (DCPA) Time (TCPA) metrics. Furthermore, DBSCAN (Density-Based Spatial Clustering Applications with Noise) clustering algorithm is employed identify suitable docking berths. Additionally, multi-source meteorological integrated data, providing more comprehensive environment. resulting system effectively combines attributes, status, event relationships, environmental factors, thereby offering robust framework supporting intelligent operations.

Language: Английский

Dynamic resilience analysis of the liner shipping network: From structure to cooperative mechanism DOI
Bo Lü,

Yue Sun,

Huipo Wang

et al.

Transportation Research Part E Logistics and Transportation Review, Journal Year: 2024, Volume and Issue: 191, P. 103755 - 103755

Published: Sept. 3, 2024

Language: Английский

Citations

7
A novel method of assessing port resilience and its positive ramifications DOI
Bingmei Gu, Jihong Chen, Hercules Haralambides

et al.

Maritime Policy & Management, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 24

Published: Jan. 19, 2025

Ports play a crucial role in facilitating global trade and logistics, serving as vital hubs that connect countries continents. However, they are susceptible to disruptions disasters due their natural characteristics, while resilience is essential for maintaining regular operations, especially the face of disruptions. From perspective inputs outputs, this study evaluates nine major Chinese ports from 2011 2021, using super-efficiency slacks-based measure network data envelopment analysis (SBM-NDEA). This approach extends beyond evaluating port's internal capacities, incorporating urban economic factors critical ensuring long-term resilience. The novel method assessing port its positive ramifications offers clearer understanding specific stages requiring improvement, thereby enhancing overall ports. Specifically, three considered: absorptive, adaptive, restorative. results reveal different exhibits distinct trends above stages. Shenzhen Port demonstrates superior performance both absorptive adaptive stages, Rizhao excels restorative stage. research contributes advancing academic knowledge industry practices by offering new insights, methodologies, practical implications

Language: Английский

Citations

0
Port resilience to climate change in the Greater Bay Area DOI Creative Commons
Zhisen Yang, Yui‐yip Lau, Mark Ching‐Pong Poo

et al.

Transportation Research Part D Transport and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 104681 - 104681

Published: March 1, 2025

Language: Английский

Citations

0
Traffic complexity assessment on the malacca strait with traffic zone matrix based on AIS data DOI Creative Commons
Dapei Liu, Zihao Liu, Hooi-Siang Kang

et al.

Ocean Engineering, Journal Year: 2024, Volume and Issue: 314, P. 119687 - 119687

Published: Nov. 4, 2024

Language: Английский

Citations

2
Independent operation or coordinated integration? Enhancing the system resilience of ports in dealing with congestion based on a bilateral bargaining game DOI
Jihong Chen,

Tingfang Li,

Huida Zhao

et al.

Ocean & Coastal Management, Journal Year: 2024, Volume and Issue: 259, P. 107437 - 107437

Published: Oct. 25, 2024

Language: Английский

Citations

1
Port vulnerability to natural disasters: An integrated view from hinterland to seaside DOI
Chengkun Li,

Xiyi Yang,

Dong Yang

et al.

Transportation Research Part D Transport and Environment, Journal Year: 2024, Volume and Issue: 139, P. 104563 - 104563

Published: Dec. 15, 2024

Language: Английский

Citations

1
Assessing port cluster resilience: Integrating hypergraph-based modeling and agent-based simulation DOI
Lingyue Li, Chunzhu Wei, Jing Liu

et al.

Transportation Research Part D Transport and Environment, Journal Year: 2024, Volume and Issue: unknown, P. 104459 - 104459

Published: Oct. 1, 2024

Language: Английский

Citations

1
Coupling and Coordination Model of Port Resilience and Urban Resilience: A Case Study Guangxi Port City Cluster Along the Pinglu Canal DOI
Tommy Dang, Siwei Li,

Liying Song

et al.

Lecture notes in civil engineering, Journal Year: 2024, Volume and Issue: unknown, P. 184 - 193

Published: Nov. 13, 2024

Language: Английский

Citations

0
Maritime Traffic Knowledge Discovery via Knowledge Graph Theory DOI Creative Commons
Shibo Li, Jiajun Xu, Xinqiang Chen

et al.

Journal of Marine Science and Engineering, Journal Year: 2024, Volume and Issue: 12(12), P. 2333 - 2333

Published: Dec. 19, 2024

Intelligent ships are a key focus for the future development of maritime transportation, relying on efficient decision-making and autonomous control within complex environments. To enhance perception, prediction, capabilities these ships, present study proposes novel approach constructing time-series knowledge graph, utilizing real-time Automatic Identification System (AIS) data analyzed via sliding window technique. By integrating advanced technologies such as extraction, representation learning, semantic fusion, both static dynamic navigational systematically unified graph. The specifically targets extraction modeling critical events, including variations in ship speed, course changes, vessel encounters, port entries exits. evaluate urgency mathematical algorithms applied to Distance Closest Point Approach (DCPA) Time (TCPA) metrics. Furthermore, DBSCAN (Density-Based Spatial Clustering Applications with Noise) clustering algorithm is employed identify suitable docking berths. Additionally, multi-source meteorological integrated data, providing more comprehensive environment. resulting system effectively combines attributes, status, event relationships, environmental factors, thereby offering robust framework supporting intelligent operations.

Language: Английский

Citations

0