Machine Learning Approaches for EV Charging Management: A Systematic Literature Review-Reference-Cited by-同舟云学术

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Machine Learning Approaches for EV Charging Management: A Systematic Literature Review

Published:2023-09-16 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings)
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Author:

Thwany Hanan¹,Alolaiwy Muhammad²,Zohdy Mohamed²,Edwards William¹,Kobus Chris J.³

Affiliation:

1. Oakland University,Industrial and Systems Engineering Department,Rochester,Michigan,USA

2. Oakland University,Electrical and Computer Engineering Department,Rochester,Michigan,USA

3. Oakland University,Mechanical Engineering Department,Rochester,Michigan,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10292429/10291015/10292487.pdf?arnumber=10292487

Reference28 articles.

1. A-Stock Price Fluctuation Forecast Model Based on LSTM

2. LSTM Based Short-term Electricity Consumption Forecast with Daily Load Profile Sequences

3. The role of renewable energy and urbanization towards greenhouse gas emission in top Asian countries: Evidence from advance panel estimations

4. Truck Parking Occupancy Prediction: XGBoost-LSTM Model Fusion

5. Neighbor-Based Optimized Logistic Regression Machine Learning Model For Electric Vehicle Occupancy Detection

Cited by 1 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. Smart EV Charging With Context-Awareness: Enhancing Resource Utilization via Deep Reinforcement Learning;IEEE Access;2024

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