Spatiotemporal Clustering of Parking Lots at the City Level for Efficiently Sharing Occupancy Forecasting Models

Miratul Khusna Mufida, Abdessamad Ait El Cadi, Thierry Delot, Martin Trépanier and Dorsaf Zekri

Article (2023)

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Department:	Department of Mathematics and Industrial Engineering
Research Center:	CIRRELT - Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation
PolyPublie URL:	https://publications.polymtl.ca/53809/
Journal Title:	Sensors (vol. 23, no. 11)
Publisher:	MDPI
DOI:	10.3390/s23115248
Official URL:	https://doi.org/10.3390/s23115248
Date Deposited:	10 Jul 2023 16:30
Last Modified:	25 Sep 2024 16:45

Cite in APA 7:	Mufida, M. K., Ait El Cadi, A., Delot, T., Trépanier, M., & Zekri, D. (2023). Spatiotemporal Clustering of Parking Lots at the City Level for Efficiently Sharing Occupancy Forecasting Models. Sensors, 23(11), 5248 (25 pages). https://doi.org/10.3390/s23115248
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