Probabilistic Electric Vehicle Charging Demand Forecast Based on Deep Learning and Machine Theory of Mind
Author:
Funder
National Natural Science Foundation of China
Beijing National Research Center for Information Science and Technology
EPSRC
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9490020/9490033/09490147.pdf?arnumber=9490147
Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Electric Vehicle Supply Equipment Day-Ahead Power Forecast Based on Deep Learning and the Attention Mechanism;IEEE Transactions on Intelligent Transportation Systems;2024-08
2. Data-Driven Short-Term Electric Vehicle Charging Station Demand Forecasting;2024 IEEE 7th International Electrical and Energy Conference (CIEEC);2024-05-10
3. Software Defined Networking Assisted Electric Vehicle Charging: Towards Smart Charge Scheduling and Management;IEEE Transactions on Network Science and Engineering;2024-01
4. STPNet: Quantifying the Uncertainty of Electric Vehicle Charging Demand via Long-Term Spatiotemporal Traffic Flow Prediction Intervals;IEEE Transactions on Intelligent Transportation Systems;2023-12
5. Self-supervised online learning algorithm for electric vehicle charging station demand and event prediction;Journal of Energy Storage;2023-11
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