Predicting Electric Vehicle Charging Stations Occupancy: A Federated Deep Learning Framework-Reference-Cited by-同舟云学术

Predicting Electric Vehicle Charging Stations Occupancy: A Federated Deep Learning Framework

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)
language:
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Author:

Douaidi Lydia¹,Senouci Sidi-Mohammed¹,El Korbi Ines¹,Harrou Fouzi²

Affiliation:

1. University of Burgundy,DRIVE Lab,Nevers,France

2. King Abdullah University of Science and Technology (KAUST),Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division,Thuwal,Saudi Arabia,23955-6900

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10199114/10199145/10199832.pdf?arnumber=10199832

Reference17 articles.

1. Forecasting bev charging station occupancy at work places;motz;GI-Jahrestagung,2020

2. Forecasting of electrical vehicle impact on infrastructure: Markov chains model of charging stations occupation

3. Federated learning for mobile keyboard prediction;hard,2018

4. Short-term forecast of ev charging stations occupancy probability using big data streaming analysis;soldan,2021

5. ACN-Data

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