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Title	Using Historical Data To Predict Parking Occupancy
ID_Doc	60558
Authors	Chawathe S.S.
Year	2019
Published	2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019
DOI	http://dx.doi.org/10.1109/UEMCON47517.2019.8993084
Abstract	This paper describes methods that use historical data on the rates of occupancy of car parking facilities to predict future occupancy rates. The methods are evaluated using a publicly available dataset of car park occupancy rates. The results suggest that a usable level of prediction accuracy may be achieved using only a modest amount of data that is easy to gather using current technologies. © 2019 IEEE.
Author Keywords	Car Parking; Intelligent Transportation Systems; Machine Learning; Regression; Smart Cities

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