Title: Demand Forecasting of a Public Bike-Sharing System Reflecting Dynamic Spatial Data
Language: English
Authors: Lee, Jiwon 
Kim, Jiyoung 
Yu, Kiyun
Issue Date: 2019
Abstract: 
Bike sharing is booming in Korea as a leisure traffic mode, but its original purpose was to reduce traffic congestion. This study developed a demand forecasting model for bike sharing connected to a subway station. For accurate demand forecasting, we used various kinds of data to reflect the spatial distribution of travel demand. We used machine learning method as prediction model, and random forest had the best predictive result.
Keywords: Public Bike-sharing System; Social Media; Random Forest
URI: https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:3-7049
http://hdl.handle.net/20.500.12708/678
DOI: 10.34726/lbs2019.51
Library ID: AC15512991
Organisation: E120 - Department für Geodäsie und Geoinformation 
Publication Type: Inproceedings
Konferenzbeitrag
Appears in Collections:Conference Paper

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