| 1 |
Refining data-driven soft sensor modeling framework with variable time reconstruction
Yao L, Ge ZQ
Journal of Process Control, 87, 91, 2020 |
| 2 |
Streaming parallel variational Bayesian supervised factor analysis for adaptive soft sensor modeling with big process data
Yang ZY, Yao L, Ge ZQ
Journal of Process Control, 85, 52, 2020 |
| 3 |
Multiple-Model State Estimation Based on Variational Bayesian Inference
Ma YJ, Zhao SY, Huang B
IEEE Transactions on Automatic Control, 64(4), 1679, 2019 |
| 4 |
Robust functional regression for wind speed forecasting based on Sparse Bayesian learning
Wang Y, Wang HB, Srinivasan D, Hu QH
Renewable Energy, 132, 43, 2019 |
| 5 |
Variational Bayesian approach for ARX systems with missing observations and varying time-delays
Chen J, Huang B, Ding F, Gu Y
Automatica, 94, 194, 2018 |
| 6 |
Correlation aware multi-step ahead wind speed forecasting with heteroscedastic multi-kernel learning
Wang Y, Xie ZX, Hu QH, Xiong SH
Energy Conversion and Management, 163, 384, 2018 |
| 7 |
A Novel Adaptive Kalman Filter With Inaccurate Process and Measurement Noise Covariance Matrices
Huang YL, Zhang YG, Wu ZM, Li N, Chambers J
IEEE Transactions on Automatic Control, 63(2), 594, 2018 |
| 8 |
Approaches to robust process identification: A review and tutorial of probabilistic methods
Kodamana H, Huang B, Ranjan R, Zhao YJ, Tan RM, Sammaknejad N
Journal of Process Control, 66, 68, 2018 |
| 9 |
Variational Bayesian Adaptive Cubature Information Filter Based on Wishart Distribution
Dong P, Jing ZL, Leung H, Shen K
IEEE Transactions on Automatic Control, 62(11), 6051, 2017 |
| 10 |
Two layered mixture Bayesian probabilistic PCA for dynamic process monitoring
Raveendran R, Huang B
Journal of Process Control, 57, 148, 2017 |
