| Artificial neural network–based machine learning approach to improve orbit prediction accuracy H Peng, X Bai Journal of Spacecraft and Rockets 55 (5), 1248-1260, 2018 | 103 | 2018 |
| Improving orbit prediction accuracy through supervised machine learning H Peng, X Bai Advances in Space Research 61 (10), 2628-2646, 2018 | 85 | 2018 |
| Exploring capability of support vector machine for improving satellite orbit prediction accuracy H Peng, X Bai Journal of Aerospace Information Systems 15 (6), 366-381, 2018 | 48 | 2018 |
| Comparative evaluation of three machine learning algorithms on improving orbit prediction accuracy H Peng, X Bai Astrodynamics 3, 325-343, 2019 | 45 | 2019 |
| Machine learning approach to improve satellite orbit prediction accuracy using publicly available data H Peng, X Bai The Journal of the astronautical sciences 67 (2), 762-793, 2020 | 41 | 2020 |
| Stability of two groups of multi-revolution elliptic halo orbits in the elliptic restricted three-body problem H Peng, S Xu Celestial Mechanics and Dynamical Astronomy 123, 279-303, 2015 | 37 | 2015 |
| Gaussian processes for improving orbit prediction accuracy H Peng, X Bai Acta astronautica 161, 44-56, 2019 | 31 | 2019 |
| Continuation of periodic orbits in the Sun-Mercury elliptic restricted three-body problem H Peng, X Bai, S Xu Communications in Nonlinear Science and Numerical Simulation 47, 1-15, 2017 | 23 | 2017 |
| Limits of Machine Learning Approach on Improving Orbit Prediction Accuracy using Support Vector Machine H Peng, X Bai Advanced Maui Optical and Space Surveillance Technologies (AMOS) Conference, 15, 2017 | 22* | 2017 |
| Transfer to a multi-revolution elliptic halo orbit in Earth–Moon elliptic restricted three-body problem using stable manifold H Peng, S Xu Advances in Space Research 55 (4), 1015-1027, 2015 | 22 | 2015 |
| Low-energy transfers to a Lunar multi-revolution elliptic halo orbit H Peng, S Xu Astrophysics and Space Science 357, 1-15, 2015 | 19 | 2015 |
| Halo orbit station-keeping using nonlinear MPC and polynomial optimization G Misra, H Peng, X Bai 2018 Space Flight Mechanics Meeting, 1454, 2018 | 18 | 2018 |
| Recovering area-to-mass ratio of resident space objects through data mining H Peng, X Bai Acta astronautica 142, 75-86, 2018 | 18 | 2018 |
| Gaussian-Binary classification for resident space object maneuver detection Y Wang, X Bai, H Peng, G Chen, D Shen, E Blasch, CB Sheaff Acta Astronautica 187, 438-446, 2021 | 17 | 2021 |
| Covariance fusion strategy of gaussian processes covariance and orbital prediction uncertainty H Peng, X Bai AAS/AIAA Astrodynamics Specialist Conference, 2019, 3647-3666, 2020 | 17 | 2020 |
| Fusion of a machine learning approach and classical orbit predictions H Peng, X Bai Acta astronautica 184, 222-240, 2021 | 16 | 2021 |
| Natural deep space satellite constellation in the Earth-Moon elliptic system H Peng, X Bai Acta astronautica 153, 240-258, 2018 | 12 | 2018 |
| Libration transfer design using patched elliptic three-body models and graphics processing units H Peng, X Bai, JJ Masdemont, G Gómez, S Xu Journal of guidance, control, and dynamics 40 (12), 3155-3166, 2017 | 11 | 2017 |
| Maintenance of libration point orbit in elliptic Sun–Mercury model H Peng, Y Liao, X Bai, S Xu IEEE transactions on aerospace and electronic systems 54 (1), 144-158, 2017 | 11 | 2017 |
| Calibration of atmospheric density model based on Gaussian Processes T Gao, H Peng, X Bai Acta astronautica 168, 273-281, 2020 | 10 | 2020 |
Xiaoli BaiRutgers, The State University of New JerseyVerified email at rutgers.edu
