首页|Findings from Georgia Technical Research Institute Provides New Data about Machi ne Learning (Identifying Cislunar Orbital Families Via Machine Learning On Light Curves)
Findings from Georgia Technical Research Institute Provides New Data about Machi ne Learning (Identifying Cislunar Orbital Families Via Machine Learning On Light Curves)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting originating in Atlanta, Georgia, by NewsRx journalists, research stated, “Current methods of performing Initial Orbi t Determination (IOD) in near-earth orbital regions cannot be directly extended to cislunar space due to changes in gravitational models that must be utilized. For the case of cislunar orbits, the Moon’s gravitational influence necessitates that orbital motions be described by three-body dynamics.” Funders for this research include Research Institute, Georgia Institute of Techn ology, GTRI’s Independent Research and Development (IRAD) funds.
AtlantaGeorgiaUnited StatesNorth a nd Central AmericaCyborgsEmerging TechnologiesMachine LearningGeorgia Te chnical Research Institute
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