Efficient and scalable DBSCAN framework for clustering continuous trajectories in road networks-Reference-Cited by-同舟云学术

Efficient and scalable DBSCAN framework for clustering continuous trajectories in road networks

Published:2023-06-01 Issue:8 Volume:37 Page:1693-1727
ISSN:1365-8816
Container-title:International Journal of Geographical Information Science
language:en
Short-container-title:International Journal of Geographical Information Science

Author:

Chen Bi Yu¹²³,Luo Yu-Bo¹²³,Zhang Yu¹²³,Jia Tao³⁴,Chen Hui-Ping¹²³,Gong Jianya¹²³,Li Qingquan¹⁵

Affiliation:

1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

2. Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan, China

3. Geocomputation Center for Social Sciences, Wuhan University, Wuhan, China

4. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

5. Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen, China

Funder

National Key Research and Development Program

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Natural Science Foundation of Hubei Province

LIESMARS special Research Funding

Publisher

Informa UK Limited

Subject

Library and Information Sciences,Geography, Planning and Development,Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/13658816.2023.2217443

Reference40 articles.

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2. Berndt, D.J. and Clifford, J., 1994. Using dynamic time warping to find patterns in time series.In: U.M. Fayyad and R. Uthurusamy, eds.Proceedings of the 3rd international conference on knowledge discovery and data mining. Seattle, WA: AAAI Press, 359–370.

3. Review and Perspective for Distance-Based Clustering of Vehicle Trajectories

4. Estimating Real-Time Traffic Carbon Dioxide Emissions Based on Intelligent Transportation System Technologies

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