TY - GEN
T1 - Data-driven cognitive modeling and semantic reasoning of ship behavior
AU - Song, Rongxin
AU - Wen, Yuanqiao
AU - Huang, Liang
AU - Zhang, Fan
AU - Zhou, Chunhui
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85140963093&partnerID=8YFLogxK
U2 - 10.1201/9781003216582-30
DO - 10.1201/9781003216582-30
M3 - Conference contribution
AN - SCOPUS:85140963093
SN - 9780367773748
T3 - Developments in Maritime Technology and Engineering - Proceedings of the 5th International Conference on Maritime Technology and Engineering, MARTECH 2020
SP - 269
EP - 276
BT - Developments in Maritime Technology and Engineering - Proceedings of the 5th International Conference on Maritime Technology and Engineering, MARTECH 2020
A2 - Soares, C. Guedes
A2 - Santos, T.A.
PB - CRC Press / Balkema - Taylor & Francis Group
T2 - 5th International Conference on Maritime Technology and Engineering, MARTECH 2020
Y2 - 16 November 2020 through 19 November 2020
ER -