Graph-Enabled Reinforcement Learning for Time Series Forecasting With Adaptive Intelligence-Reference-Cited by-同舟云学术

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Graph-Enabled Reinforcement Learning for Time Series Forecasting With Adaptive Intelligence

Published:2024-08 Issue:4 Volume:8 Page:2908-2918
ISSN:2471-285X
Container-title:IEEE Transactions on Emerging Topics in Computational Intelligence
language:
Short-container-title:IEEE Trans. Emerg. Top. Comput. Intell.

Author:

Shaik Thanveer¹^ORCID,Tao Xiaohui¹^ORCID,Xie Haoran²^ORCID,Li Lin³^ORCID,Yong Jianming⁴^ORCID,Li Yuefeng⁵^ORCID

Affiliation:

1. School of Mathematics, Physics & Computing, University of Southern Queensland, Toowoomba, QLD, Australia

2. Department of Computing and Decision Sciences, Lingnan University, Tuen Mun, Hong Kong

3. School of Computer and Artificial Intelligence, Wuhan University of Technology, Wuhan, China

4. School of Business, University of Southern Queensland, Toowoomba, QLD, Australia

5. School of Computer Science, Queensland University of Technology, Brisbane, QLD, Australia

Funder

Australian Research Council's Discovery Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7433297/10607834/10530910.pdf?arnumber=10530910

Reference39 articles.

1. Shifting machine learning for healthcare from development to deployment and from models to data

2. AI enabled RPM for mental health facility

3. FedStack: Personalized activity monitoring using stacked federated learning

4. A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification

5. Can the artificial intelligence technique of reinforcement learning use continuously-monitored digital data to optimize treatment for weight loss?

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