Data-driven cognitive modeling and semantic reasoning of ship behavior

Conference Paper (2021)
Author(s)

Rongxin Song (Wuhan University of Technology)

Yuanqiao Wen (Wuhan University of Technology)

Liang Huang (Wuhan University of Technology)

Fan Zhang (Wuhan University of Technology)

Chunhui Zhou (Wuhan University of Technology)

Affiliation
External organisation
DOI related publication
https://doi.org/10.1201/9781003216582-30
More Info
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Publication Year
2021
Language
English
Affiliation
External organisation
Pages (from-to)
269-276
ISBN (print)
9780367773748

Abstract

Aiming at the cognition problem of systematic ship behavior in harbor, a behavior recognition model based on semantic reasoning based on discrete event system modeling theory was proposed. Firstly, the hierarchical modeling of the behavior of ships in port waters is divided into data layer, event layer, activity layer and process layer. Based on a certain theoretical understanding of ship behavior on different time scales and space scales, build a ship behavior cognitive model; Secondly, in the data layer, the trajectory key point detection and segmentation extraction of the motion trajectory of port ship AIS data are performed by integrating port navigation rules to realize the labeling of ship trajectories. Finally, based on the labeling results of the data layer, the ontology is used to make inferences to discover the implicit ship behavior, and realize the trajectory of the ship from the data layer to the semantic layer. Experiments were performed using Xiamen Port data. The experimental results show that the behavioral cognitive ontology based on discrete system modeling can realize the cognitive and semantic reasoning of ship behavior at different time and space scales.

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