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Regression Model for Bike-Sharing Service by Using Machine Learning

Asian Journal of Social Science Studies

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Title Regression Model for Bike-Sharing Service by Using Machine Learning
 
Creator Wang, Zhifeng
 
Description The bike sharing system has brought wide convenience to residents in the city and serves as important tools to transport from one place to another place. For the bike sharing companies, they need to know the total users of bike, so they can release suitable number of bikes into the market. This paper uses visualization technology to visualize data and figure out the possible factors which can impact the total number of users. After completing the data analyzing, this paper figures out the season, weather sit, feeling temperature, humanity and wind speed are the main factors which can have impacts on the total number of users. In the second stages, this paper uses regression model, NN model, ELM model and DELM model to predict the possible number of bike users. The input factors are season, weather sit, feeling temperature, humanity and wind speed. By analyzing regression model results, the ELM model has the best prediction, which can be used for real practice.
 
Publisher July Press Pte. Ltd.
 
Contributor —
 
Date 2019-11-06
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://journal.julypress.com/index.php/ajsss/article/view/666
10.20849/ajsss.v4i4.666
 
Source Asian Journal of Social Science Studies; Vol 4, No 4 (2019); p16
2424-9041
2424-8517
 
Language eng
 
Relation http://journal.julypress.com/index.php/ajsss/article/view/666/487
 
Rights Copyright (c) 2019 Zhifeng Wang
http://creativecommons.org/licenses/by/4.0