Wang, H., Shen, H. and Ouyang, W. (2018) Exploiting POI-Specific Geographical Influence for Point-of-Interest Recommendation. Proceedings of the 27th International Joint Conference on Artificial Intelligence, Stockholm, 13-19 July 2018, 3877-3883.
https://doi.org/10.24963/ijcai.2018/539

has been cited by the following article:

• TITLE: A Prediction Method of Charging Station Planning Based on BP Neural Network

  AUTHORS: Jia Xu, Jing Li, Xin Liao, Changping Song

  KEYWORDS: Electric Vehicle Charging Station, BP Neural Network, Location, Capacity Prediction

  JOURNAL NAME: Journal of Computer and Communications, Vol.7 No.7, July 24, 2019

  ABSTRACT: The construction of charging service facilities is a very important factor in the popularization of electric vehicles. Therefore, the planning problems of electric vehicle charging station are urgent to be solved. Considering the standard of natural environment, society, traffic, power grid and economy, an evaluation system is created for electric vehicle charging station project through 15 sub-standards. Planning model of charging station is constructed based on BP neural network adopted in the analysis. It is used for location and capacity prediction of charging station planning. By analyzing the model with data samples, a stable network structure is established and the feasibility of the model is verified in the charging station planning.