In-Flight Energy-Driven Composition of Drone

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dc.contributor.authorAbdelhafid, Souad
dc.contributor.authorSayad, Lamri: supervisor
dc.date.accessioned2024-07-10T13:03:40Z
dc.date.available2024-07-10T13:03:40Z
dc.date.issued2023-09
dc.description.abstractThis project explores the innovative concept of In-Flight Energy-Driven Composition of Drones to improve the capabilities and sustainability of unmanned aerial vehicles (UAVs). By harnessing renewable energy sources such as solar cells and using genetic algorithms in Python, the goal is to optimize the in-flight composition of drones, resulting in longer operational life, lower carbon emissions, and increased payload capacity.
dc.identifier.urihttps://dspace.univ-msila.dz/handle/123456789/43578
dc.language.isoen
dc.publisherMohamed Boudiaf University of M'sila
dc.subjectUAVs (Unmanned Aerial Vehicles)
dc.subjectGenetic Algorithms
dc.subjectMATHEMATICS::Applied mathematics::Optimization, systems theory
dc.titleIn-Flight Energy-Driven Composition of Drone
dc.typeThesis

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