Predicting electric vehicle charging demand using a heterogeneous spatio-temporal graph convolutional network
Abstract Short-term Electric Vehicle (EV) charging demand prediction is an essential task in
the fields of smart grid and intelligent transportation systems, as understanding the …
the fields of smart grid and intelligent transportation systems, as understanding the …
Predicting electric vehicle charging demand using a heterogeneous spatio-temporal graph convolutional network
S Wang, A Chen, P Wang, C Zhuge - Transportation Research Part C …, 2023 - trid.trb.org
Short-term Electric Vehicle (EV) charging demand prediction is an essential task in the fields
of smart grid and intelligent transportation systems, as understanding the spatiotemporal …
of smart grid and intelligent transportation systems, as understanding the spatiotemporal …
Predicting electric vehicle charging demand using a heterogeneous spatio-temporal graph convolutional network
S Wang, A Chen, P Wang… - … Research Part C …, 2023 - ui.adsabs.harvard.edu
Propose a spatial–temporal graph conventional network to predict charging demand; Train
the model with a large private electric vehicle trajectory dataset; Our model outperforms …
the model with a large private electric vehicle trajectory dataset; Our model outperforms …
Predicting electric vehicle charging demand using a heterogeneous spatio-temporal graph convolutional network
S Wang, A Chen, P Wang… - … Research Part C …, 2023 - research.polyu.edu.hk
Abstract Short-term Electric Vehicle (EV) charging demand prediction is an essential task in
the fields of smart grid and intelligent transportation systems, as understanding the …
the fields of smart grid and intelligent transportation systems, as understanding the …