A data-driven iterative learning approach for optimizing the train control strategy-Reference-Cited by-同舟云学术

A data-driven iterative learning approach for optimizing the train control strategy

Published:2022 Issue: Volume: Page:1-8
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Su Shuai¹^ORCID,Zhu Qingyang¹^ORCID,Liu Junqing¹,Tang Tao¹^ORCID,Wei Qinglai²^ORCID,Cao Yuan¹^ORCID

Affiliation:

1. State Key Laboratory of Rail Traffic Control and Safety and Frontiers Science Center for Smart High-speed Railway System, Beijing Jiaotong University, Beijing, China

2. School of Artificial Intelligence, University of Chinese Academy of Sciences, State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9424/4389054/09847351.pdf?arnumber=9847351

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