Multi-feature data fusion-based load forecasting of electric vehicle charging stations using a deep learning model

HIGHLIGHTS

• who: Prince Aduama and collaborators from the Department of Electrical Engineering and Computer Science, Khalifa University of Science and Technology have published the research work: Multi-Feature Data Fusion-Based Load Forecasting of Electric Vehicle Charging Stations Using a Deep Learning Model, in the Journal: Energies 2023, 16, x FOR PEER REVIEW of /2023/
• what: The authors propose a forecasting technique based on multi-feature data fusion to enhance the accuracy of an (EV) station load forecasting deep-learning model. In , a graph convolution network model was implemented to determine the level of use of . . .
  

   

  

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