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LoTAD: long-term traffic anomaly detection based on crowdsourced bus trajectory data

Crossref DOI link: https://doi.org/10.1007/s11280-017-0487-4

Published Online: 2017-08-10

Published Print: 2018-05

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Kong, Xiangjie

Song, Ximeng

Xia, Feng

Guo, Haochen

Wang, Jinzhong

Tolba, Amr
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (61572106)

Natural Science Foundation of Liaoning Province (201602154)

Dalian Science and Technology Planning Project (2015A11GX015)

Dalian Science and Technology Planning Project (2015R054)
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Text and Data Mining valid from 2017-08-10
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Article History

Received: 29 January 2017

Revised: 27 May 2017

Accepted: 25 July 2017

First Online: 10 August 2017