… of this type of vehicles. In this paper, we only consider Electric Vehicles (EVs), ie, those 100%
… by electricity, and Plug-In Hybrid Electric Vehicles (PHEVs), while obviating Hybrid Electric …

… At the moment, our framework relates to user behavior predictions for electric vehicles;
however, we believe that our network has the potential to be adapted to other applications. It …

… of electric vehicles (EVs) connected to the grid increases, the EV electricity demand rises …
Therefore, accurate spatial–temporal distribution prediction of EV charging load is vital for …

… The major contribution of this paper lies in presenting an accurate methodology for predicting
the electric vehicle power consumption on a known route by combining a driver model and …

… We propose a novel hierarchical model for optimizing electric vehicle (EV) charging
infrastructure deployment. The key innovation is using an ensemble time series forecasting …

… ) approach for better prediction of electric vehicles (EVs) energy … , which enhances the
model prediction and decreases the model … Tackling the challenge of predicting EVs’ energy …

… of [6] implicate that predicting the user behavior yields higher … and ED prediction for intelligent
charging on vehicle arrival. … DT predictions and the underestimated ED predictions, we …

… of electric vehicles (EVs). To address the problem of range anxiety, this paper presents an
energy consumption prediction … This method allows for prediction of energy consumption over …

… from heterogeneous urban open data) for bike trip demand prediction is applied. In [17], it is
… In the electric vehicle domain, often, mobility data are used to estimate future demand. In [14]…

… Jun, “Review of electric vehicle charging demand forecasting … load forecasting methods for
electric vehicle charging station,… algorithm on the prediction of electric vehicle charging load,” …