Enhancing IoT Intelligence: A Transformer-based Reinforcement Learning Methodology-Reference-Cited by-同舟云学术

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Enhancing IoT Intelligence: A Transformer-based Reinforcement Learning Methodology

Published:2024-05-27 Issue: Volume:35 Page:1418-1423
ISSN:
Container-title:2024 International Wireless Communications and Mobile Computing (IWCMC)
language:
Short-container-title:

Author:

Rjoub Gaith¹,Islam Saidul²,Bentahar Jamal³,Almaiah Mohammed Amin⁴,Alrawashdeh Rana⁵

Affiliation:

1. Aqaba University of Technology,Faculty of Information Technology,Aqaba,Jordan

2. Concordia Institute for Information Systems Engineering, Concordia University,Montreal,Canada

3. Khalifa University,Department of Computer Science,Abu Dhabi,UAE

4. The University of Jordan,King Abdullah II School of Information Technology,Amman,Jordan

5. King Fahd University of Petroleum & Minerals,Department of Information and Computer Science,Dhahran,KSA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592105/10592309/10592607.pdf?arnumber=10592607

Reference23 articles.

1. A comprehensive survey on applications of transformers for deep learning tasks

2. A new method of hybrid time window embedding with transformer-based traffic data classification in IoT-networked environment

3. A Survey on Explainable Artificial Intelligence for Cybersecurity

4. Improving Autonomous Vehicles Safety in Snow Weather Using Federated YOLO CNN Learning

5. A multi-head attention-based transformer model for traffic flow forecasting;Reza,2018

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