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Ship Trajectory Reconstruction from AIS Sensory Data via Data Quality Control and Prediction
Joint Authors
Chen, Xinqiang
Ling, Jun
Yang, Yongsheng
Zheng, Hailin
Xiong, Pengwen
Xiong, Yong
Postolache, Octavian Adrian
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-17
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Accurate ship trajectory plays an important role for maritime traffic control and management, and ship trajectory prediction with Automatic Identification System (AIS) data has attracted considerable research attentions in maritime traffic community.
The raw AIS data may be contaminated by noises, which limits its usage in maritime traffic management applications in real world.
To address the issue, we proposed an ensemble ship trajectory reconstruction framework combining data quality control procedure and prediction module.
More specifically, the proposed framework implemented the data quality control procedure in three steps: trajectory separation, data denoising, and normalization.
In greater detail, the data quality control procedure firstly identified outliers from the raw ship AIS data sample, which were further cleansed with the moving average model.
Then, the denoised data were normalized into evenly distributed data series (in terms of time interval).
After that, the proposed framework predicted ship trajectory with the artificial neural network.
We verified the proposed model performance with two ship trajectories downloaded from public accessible AIS data base.
American Psychological Association (APA)
Chen, Xinqiang& Ling, Jun& Yang, Yongsheng& Zheng, Hailin& Xiong, Pengwen& Postolache, Octavian Adrian…[et al.]. 2020. Ship Trajectory Reconstruction from AIS Sensory Data via Data Quality Control and Prediction. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1197752
Modern Language Association (MLA)
Chen, Xinqiang…[et al.]. Ship Trajectory Reconstruction from AIS Sensory Data via Data Quality Control and Prediction. Mathematical Problems in Engineering No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1197752
American Medical Association (AMA)
Chen, Xinqiang& Ling, Jun& Yang, Yongsheng& Zheng, Hailin& Xiong, Pengwen& Postolache, Octavian Adrian…[et al.]. Ship Trajectory Reconstruction from AIS Sensory Data via Data Quality Control and Prediction. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1197752
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1197752