Modeling Longitudinal Evolution of Decommissioned Geostationary Satellites using Neural Networks
İbrahim Öz,
Cevat Özarpa
Abstract:This study uses neural networks to explore the intricate longitudinal progression of decommissioned geostationary satellites. The goal is to model and predict satellites' longitudinal dynamics across time dimensions. Historical satellite longitude data undergoes thorough preprocessing to train time series neural networks in both single-input and 3-input configurations for all six decommissioned satellites, yielding comprehensive longitudinal behavior insights. Results reveal impressive outcomes: average Mean S… Show more
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