Classical versus reinforcement learning algorithms for unmanned aerial vehicle network communication and coverage path planning: A systematic literature review-Reference-Cited by-同舟云学术

Classical versus reinforcement learning algorithms for unmanned aerial vehicle network communication and coverage path planning: A systematic literature review

Published:2022-12-28 Issue:5 Volume:36 Page:
ISSN:1074-5351
Container-title:International Journal of Communication Systems
language:en
Short-container-title:Int J Communication

Author:

Mannan Abdul¹²,Obaidat Mohammad S.³⁴,Mahmood Khalid⁵,Ahmad Aftab⁶,Ahmad Rodina¹

Affiliation:

1. Faculty of Computer Science & Information Technology University of Malaya Kuala Lumpur Malaysia

2. Department of Computer Science Bahauddin Zakariya University Multan Pakistan

3. Chair & Professor, Computer Science Department, and Director of Cybersecurity Center University of Texas‐Permian Basin Odessa Texas USA

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

5. Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Yunlin ROC Taiwan

6. Department of Electronics National Yunlin University of Science and Technology Yunlin ROC Taiwan

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/dac.5423

Reference156 articles.

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3. A survey on coverage path planning for robotics

4. On complete coverage path planning algorithms for non‐holonomic mobile robots: Survey and challenges;Khan A;J Inf Sci Eng,2017

5. KimD‐H FarhadA PyunJ‐Y.UWB positioning system based on LSTM classification with mitigated NLOS effects. IEEE Internet of Things Journal;2022.

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