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Hao Peng
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Limits of Machine Learning Approach on Improving Orbit Prediction Accuracy
Covariance Fusion Method of Gaussian Processes Covariance and Orbital Prediction Uncertainty (Accepted)
Gaussian Processes for Improving Orbit Prediction Accuracy
Machine Learning Approach to Improve Satellite Orbit Prediction Accuracy Using Publicly Available Data
Comparative Evaluation of Three Machine Learning Algorithms on Improving Orbit Prediction Accuracy (Accepted)
Natural Deep Space Satellite Constellation in the Earth-Moon Elliptic System
Comparison of Effective Machine Learning Algorithms on Improving Orbit Prediction Accuracy
Artificial Neural Network–Based Machine Learning Approach to Improve Orbit Prediction Accuracy
Generalization Capability of Machine Learning Approach Among Different Satellites: Validated Using TLE Data
Obtain Confidence Interval for the Machine Learning Approach to Improve Orbit Prediction Accuracy
Exploring Capability of Support Vector Machine for Improving Satellite Orbit Prediction Accuracy
A Machine Learning Approach to Improve Satellite Orbit Prediction Accuracy: Validation Using Publicly Available Data
Improving Orbit Prediction Accuracy Through Supervised Machine Learning
Halo Orbit Station-Keeping Using Nonlinear MPC and Polynomial Optimization
Recovering Area-to-Mass Ratio of Resident Space Objects through Data Mining
Using Artificial Neural Network in Machine Learning Approach to Improve Orbit Prediction Accuracy
Libration Transfer Design Using Patched Elliptic Three-Body Models and Graphics Processing Units
Continuation of Periodic Orbits in the Sun-Mercury Elliptic Restricted Three-Body Problem
New Natural Formation Flying Configurations in the Earth-Moon Elliptic Three-Body System
Maintenance of Libration Point Orbit in Elliptic Sun-Mercury Model
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