Predicting the spatiotemporal legality of on-street parking using open data and machine learning
Author:
Affiliation:
1. Geospatial Data Science Lab, Department of Geography, University of Wisconsin—Madison, USA
2. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
3. Pace Suburban Bus, Chicago, IL, USA
Publisher
Informa UK Limited
Subject
General Earth and Planetary Sciences,Computer Science Applications
Link
https://www.tandfonline.com/doi/pdf/10.1080/19475683.2019.1679882
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