Cognitive traffic anomaly prediction from GPS trajectories using Visible Outlier Indexes and Meshed Spatiotemporal Neighborhoods

Huang, Guang-Li, Deng, Ke and He, Jing 2020, Cognitive traffic anomaly prediction from GPS trajectories using Visible Outlier Indexes and Meshed Spatiotemporal Neighborhoods, Cognitive computation, vol. 12, pp. 967-978, doi: 10.1007/s12559-020-09735-3.

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Title Cognitive traffic anomaly prediction from GPS trajectories using Visible Outlier Indexes and Meshed Spatiotemporal Neighborhoods
Author(s) Huang, Guang-LiORCID iD for Huang, Guang-Li orcid.org/0000-0001-8698-2946
Deng, Ke
He, Jing
Journal name Cognitive computation
Volume number 12
Start page 967
End page 978
Total pages 12
Publisher Springer
Place of publication Cham, Switzerland
Publication date 2020
ISSN 1866-9956
1866-9964
Keyword(s) Science & Technology
Technology
Life Sciences & Biomedicine
Computer Science, Artificial Intelligence
Neurosciences
Computer Science
Neurosciences & Neurology
Cognitive anomaly prediction
Trajectories
Abnormal levels
Visible outlier indexes
Spatiotemporal neighborhoods
Language eng
DOI 10.1007/s12559-020-09735-3
Indigenous content off
Field of Research 0801 Artificial Intelligence and Image Processing
1109 Neurosciences
1702 Cognitive Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30141585

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