Effect Analysis of Recommended Parking Spots on Bike Sharing System Based on Clustering Algorithm
- https://doi.org/10.2991/isss-18.2018.81How to use a DOI?
- Clustering algorithm, Bike sharing, Effect analyze
Bike sharing has received a rapid development in recent China since 2016. However, the side effect from huge amount of sharing bikes poured into traffic networks has caused both side effect on traffic system and the restrictions from the government. In order to reduce the negative impact, recommended parking spots are made. In this paper, we build the time cost model and use clustering algorithm to compare the system performance before and after setting up the recommendation site by abstract model from real fact
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Shikun He AU - Qiong Tian AU - Jingtao Zhang PY - 2018/05 DA - 2018/05 TI - Effect Analysis of Recommended Parking Spots on Bike Sharing System Based on Clustering Algorithm BT - Proceedings of the 4th International Symposium on Social Science (ISSS 2018) PB - Atlantis Press SP - 389 EP - 393 SN - 2352-5398 UR - https://doi.org/10.2991/isss-18.2018.81 DO - https://doi.org/10.2991/isss-18.2018.81 ID - He2018/05 ER -