Joint path planning and power allocation of a cellular-connected UAV using apprenticeship learning via deep inverse reinforcement learning-Reference-Cited by-同舟云学术

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Joint path planning and power allocation of a cellular-connected UAV using apprenticeship learning via deep inverse reinforcement learning

Published:2024-12 Issue: Volume:254 Page:110789
ISSN:1389-1286
Container-title:Computer Networks
language:en
Short-container-title:Computer Networks

Author:

Shamsoshoara Alireza^ORCID,Lotfi Fatemeh^ORCID,Mousavi Sajad,Afghah Fatemeh,Güvenç İsmail^ORCID

Funder

Air Force Office of Scientific Research

National Science Foundation

Publisher

Elsevier BV

Reference94 articles.

1. Supporting disaster relief operations through UTM: Operational concept and flight tests of unmanned and manned vehicles at a disaster drill;Andreeva-Mori,2020

2. An adaptive Flying Ad-hoc Network (FANET) for disaster response operations to improve quality of service (QoS);Pandey;Modern Phys. Lett. B,2020

3. UAV trajectory planning for disaster scenarios;Javed;Veh. Commun.,2023

4. Wildfire monitoring in remote areas using autonomous unmanned aerial vehicles;Afghah,2019

5. Aerial Imagery Pile burn detection using deep learning: the FLAME dataset;Shamsoshoara;Comput. Netw.,2021

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