Data-driven cognitive modeling and semantic reasoning of ship behavior

Song, Rongxin; Wen, Yuanqiao; Huang, Liang; Zhang, Fan; Zhou, Chunhui

doi:10.1201/9781003216582-30

Cited by 1 publication

(3 citation statements)

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“…Based on these efforts, some studies on ship semantic behaviors have also been carried out. A semantic model of ship behavior was proposed in [14], which takes into account the uncertainty of the occurring behavior; [15] mined the pattern of ship trajectories by means of semantic annotation and possibility modeling; and [1] constructed the ontology model of ship behavior, considering the temporal relationships between each other. In addition, some projects work on the semantic computing of trajectories in the maritime domain.…”

Section: Semantic Expressions Of Trajectorymentioning

confidence: 99%

“…This model provides a way to reach the goal of semantic unit formation, supporting further high-level semantic modeling for complicated behaviors, which can be represented with a set of traffic behaviors. In addition, we explored the temporal relations preliminarily within complicated behaviors in [1], where we expected to depict complicated behaviors through combining simple behaviors.…”

Section: Previous Work For Semantic Modeling Of Ship Behaviormentioning

confidence: 99%

“…This work is based on the previous work [1,2], focusing on modeling and reasoning of semantic ship behavior with different scales in multiple dimensions. We propose a semantic model to extract and recognize multi-scale behaviors automatically in cognitive space based on historical automatic identification system (AIS) data.…”

Section: Introductionmentioning

confidence: 99%

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Semantic Modeling of Ship Behavior in Cognitive Space

Song

Wen

Tao

et al. 2022

JMSE

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Ship behavior is the semantic expression of corresponding trajectory in spatial-temporal space. The intelligent identification of ship behavior is critical for safety supervision in the waterborne transport. In particular, the complicated behavior reflects the long-term intentions of a ship, but it is challenging to recognize it automatically for computers without a proper understanding. For this purpose, this study provides a method to model the behavior for computers from the perspective of knowledge modeling that is explainable. Based on our previous work, a semantic model for ship behavior representation is given considering the multi-scale features of ship behavior in cognitive space. Firstly, the multi-scale features of ship behavior are analyzed in spatial-temporal dimension and semantic dimension individually. Then, a method for multi-scale behaviors modeling from the perspective of semantics is determined, which divides the behavior scale into four sub-scales in cognitive space, considering spatial and temporal dimensions: action, activity, process, and event. Furthermore, an ontology model is introduced to construct the multi-scale semantic model for ship behavior, where behaviors with different semantic scales are expressed using the functions of ontology from a microscopic perspective to a macroscopic perspective consecutively. To validate the model, a case study is conducted in which ship behavior with different scales occurred in port water areas. Typical behaviors, which include leveraging the axioms expression and semantic web rule language (SWRL) of the ontology, are then deduced using a reasoner, such as Pellet. The results show that the model is reasonable and feasible to represent multi-scale ship behavior in various scenarios and provides the potential to construct a smart supervision network for maritime authorities.

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Section: Semantic Expressions Of Trajectorymentioning

confidence: 99%

Section: Previous Work For Semantic Modeling Of Ship Behaviormentioning

confidence: 99%