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Thus, this paper proposes initial deployment and trajectory optimization techniques for stable communication between HST and Multi-UAV with the energy ...
Thus, this paper proposes initial deployment and trajectory optimization techniques for stable communication between HST and Multi-. UAV with the energy ...
Thus, this paper proposes initial deployment and trajectory optimization techniques for stable communication between HST and Multi-UAV with the energy ...
Dive into the research topics of 'Optimized deployment of multi-UAV based on machine learning in UAV-HST networking'. Together they form a unique fingerprint.
Optimized Deployment of Multi-UAV based on Machine Learning in UAV-HST Networking. Year: 2020. Author: Yu Min Park. Co-author: Yan Kyaw Tun, Choong Seon Hong.
Optimized Deployment of Multi-UAV based on Machine Learning in UAV-HST Networking. Conference Paper. Sep 2020. Yu Min Park · Yan Kyaw Tun ...
We propose a UAV fog deployment algorithm for fog nodes deployed in rescue missions. We develop an optimization strategy for dynamic networks during evacuation ...
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This review paper provides insights into optimization strategies for Unmanned Aerial Vehicles (UAVs) in a variety of surveillance tasks and scenarios.
Park, Optimized deployment of multi-UAV based on machine learning in UAV-hst networking, с. 102; Naouri, Efficient fog node placement using nature-inspired ...
Nov 7, 2024 · To make the optimization tractable, a multi-agent CNN-enhanced deep Q learning (MA-CDQL) algorithm is proposed. The algorithm integrates a ...
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