Support Vector Machine Based Design and Simulation of Air Traffic Management for Prioritized Landing of Large Number of UAVs

Ahmed Abdulhameed and Qurban Memon
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Ahmed Abdulhameed: UAE University, UAE.
Qurban Memon: UAE University, UAE.

European Journal of Artificial Intelligence and Machine Learning, 2022, vol. 1, issue 2, 17-21

Abstract: UAVs also known as drones are gaining more popularity day by day and its applications keep increasing. They are being used in several areas, such as transportation, surveillance, defense, etc. They open doors for new innovative applications due to their compact design, flexibility in landing and departing, the accurate possible control of their flying methodology. As a part of expected future of extensive use of this device, a landing control system for prioritizing the landing of large number of UAVs at a certain station using support vector machine learning is proposed. The proposed system shows promising results in terms of controlling landing sequences of a large number of UAVs. Based on results, the conclusions are presented.

Keywords: Drone; Landing Sequences; Machine learning; Support vector machine; UAV. (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejai00:v:1:y:2022:i:2:id:1007

DOI: 10.24018/ejai.2022.1.2.7

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