| 1 |
Privacy-preserving distributed parameter estimation for probability distribution of wind power forecast error
Jia MS, Huang SW, Wang ZW, Shen C
Renewable Energy, 163, 1318, 2021 |
| 2 |
Identification of Linear Models From Quantized Data: A Midpoint-Projection Approach
Risuleo RS, Bottegal G, Hjalmarsson H
IEEE Transactions on Automatic Control, 65(7), 2801, 2020 |
| 3 |
Semi-supervised dynamic latent variable modeling: I/O probabilistic slow feature analysis approach
Fan L, Kodamana H, Huang BA
AIChE Journal, 65(3), 964, 2019 |
| 4 |
Robust optimization of a pharmaceutical freeze-drying process under non-Gaussian parameter uncertainties
Xie XZ, Schenkendorf R
Chemical Engineering Science, 207, 805, 2019 |
| 5 |
Data rectification for multiple operating modes: A MAP framework
Alighardashi H, Jan NM, Huang B
Computers & Chemical Engineering, 123, 272, 2019 |
| 6 |
Optimization of the collimator mask for the rotational modulation collimator-based gamma-ray/neutron dual-particle imager
Kim HS, Ye SJ, Lee G, Kim G
Current Applied Physics, 19(7), 856, 2019 |
| 7 |
Parameter Estimation in Switching Markov Systems and Unsupervised Smoothing
Zheng F, Derrode S, Pieczynski W
IEEE Transactions on Automatic Control, 64(4), 1761, 2019 |
| 8 |
A review of the Expectation Maximization algorithm in data-driven process identification
Sammaknejad N, Zhao YJ, Huang B
Journal of Process Control, 73, 123, 2019 |
| 9 |
Mixture modeling for industrial soft sensor application based on semi-supervised probabilistic PLS
Zheng JH, Song ZH
Journal of Process Control, 84, 46, 2019 |
| 10 |
Mixture modeling for industrial soft sensor application based on semi-supervised probabilistic PLS
Zheng JH, Song ZH
Journal of Process Control, 84, 46, 2019 |
