NDLI: An Analysis Method of Ship Traffic Section Flow Based on Big Data

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An Analysis Method of Ship Traffic Section Flow Based on Big Data

Content Provider	Scilit
Author	Yi-Fan, Liu
Copyright Year	2021
Description	Journal: Journal of Physics: Conference Series Traffic flow has important research value for traffic planning and traffic management. In waterway traffic, the cross-sectional flow of ships also has important application value in ship safety management, navigation rule making, bridge and wharf construction, and ship driver decision-making. In order to fully explore the characteristics of ship traffic flow in the big data environment, this paper studies the analysis method of ship cross-section flow based on big data. First of all, in order to ensure the accuracy of calculation and reduce the calculation time to improve calculation efficiency, based on AIS big data optimization data processing method, complete data storage strategy and construction of data management mechanism. Then, the ship section flow analysis algorithm is proposed and implemented. Finally, based on the ship section flow analysis algorithm, a ship section flow analysis and statistics system is constructed to complete the flow calculation and information statistics. The research results of this paper make the relevant analysis of ship traffic flow more convenient and faster, and have greater application value for waterway traffic planning and management.
Related Links	https://iopscience.iop.org/article/10.1088/1742-6596/1848/1/012007/pdf
ISSN	17426588
e-ISSN	17426596
DOI	10.1088/1742-6596/1848/1/012007
Journal	Journal of Physics: Conference Series
Issue Number	1
Volume Number	1848
Language	English
Publisher	IOP Publishing
Publisher Date	2021-04-01
Access Restriction	Open
Subject Keyword	Journal: Journal of Physics: Conference Series Characterization and Testing of Materials Transportation Science and Technology
Content Type	Text
Resource Type	Article
Subject	Physics and Astronomy

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