An Efficient Gated-Attention Spatiotemporal Convolutional Network for Economical Operation of Electric Vehicle Charging Stations-Reference-Cited by-同舟云学术

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An Efficient Gated-Attention Spatiotemporal Convolutional Network for Economical Operation of Electric Vehicle Charging Stations

Published:2024 Issue: Volume: Page:1-15
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Li Yiqun¹^ORCID,Zhang Xian¹^ORCID,Wang Guibin²^ORCID,Wen Fushuan³^ORCID,Pu Ziyuan⁴^ORCID,Chung Edward⁵^ORCID

Affiliation:

1. School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, China

2. College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China

3. School of Electrical Engineering, Zhejiang University, Hangzhou, China

4. School of Transportation, Southeast University, Nanjing, China

5. Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China

Funder

National Natural Science Foundation of China

Guangdong Basic and Applied Basic Research Foundation

Major Science and Technology Special Projects in Xinjiang Autonomous Region

Xinjiang Autonomous Region Key Research and Development Task Special Project

General Program of Foundation of Shenzhen Science and Technology Committee

Foundations of Shenzhen Science and Technology Committee

Hangzhou Qianjiang Distinguished Expert Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6979/4358928/10648658.pdf?arnumber=10648658

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