Data-driven multilevel ship route network construction method

Abstract

The invention provides a data-driven multilevel ship route network construction method. The method comprises the following steps: batch extraction of off-line tracks and processing of abnormal values of the tracks; carrying out adaptive threshold track compression based on a TD-TR method; identifying important track points; and constructing a multi-level air route network based on OPTICS and a graph theory. The invention provides a multi-level ship route network construction framework based on mass AIS data from the perspective of multi-layer (wharf, harbor district and harbor) and multi-dimensional (such as point, chain and network) structures. Important track points of a ship are abstracted into nodes through a clustering algorithm, and a multi-layer hierarchical route network is formed by taking representative routes among the nodes as edges based on a graph theory. The constructed multi-level air route network is not only suitable for high-level statistical analysis, but also suitable for executing low-level ship activity or behavior analysis.

Description

technical field [0001] The invention relates to the technical field of marine transportation, in particular to a data-driven multi-level ship route network construction method. Background technique [0002] With the development of the world economy, the transportation tasks of water traffic are becoming increasingly heavy, and the sea traffic routes are intertwined and increasingly complex, gradually forming a route network. The increasing availability of Automatic Identification System (AIS) data presents enormous opportunities to track ship activity and mine spatiotemporal patterns of global ship traffic. Nowadays, marine traffic research using AIS data mainly includes the generation of maritime traffic density maps, the generation of hierarchical networks of maritime routes, and the spatiotemporal interactions of different maritime activities. Among them, there are few studies on the construction of maritime route networks, and most of them are researches on the complexi...

AI Technical Summary

Problems solved by technology

The type and number of terminals in the port area (cargo owners' terminals, enterprise terminals, traditional terminals) are also increasing, so the simple construction of a shipping network with ports or cities as nodes can no longer meet the requirements, and it is impossible to fully explore the spatiotemporal behavior information and information of ships. semantic knowledge

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