| 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 |
Multimodal process monitoring based on transition-constrained Gaussian mixture model
Chen ST, Jiang QC, Yan XF
Chinese Journal of Chemical Engineering, 28(12), 3070, 2020 |
| 3 |
Remote State Estimation With Stochastic Event-Triggered Sensor Schedule and Packet Drops
Xu L, Mo YL, Xie LH
IEEE Transactions on Automatic Control, 65(11), 4981, 2020 |
| 4 |
A Robust Infinite Gaussian Mixture Model and Its Application in Fault Detection of Nonlinear Multimode Processes
Pan Y, Xie L, Su HY, Luo L
Journal of Chemical Engineering of Japan, 53(12), 758, 2020 |
| 5 |
Short-term forecasting and uncertainty analysis of wind turbine power based on long short-term memory network and Gaussian mixture model
Zhang JH, Yan J, Infield D, Liu YQ, Lien FS
Applied Energy, 241, 229, 2019 |
| 6 |
Data rectification for multiple operating modes: A MAP framework
Alighardashi H, Jan NM, Huang B
Computers & Chemical Engineering, 123, 272, 2019 |
| 7 |
Dynamic prediction of interface level using spatial temporal markov random field
Liu ZY, Kodamana H, Afacan A, Huang B
Computers & Chemical Engineering, 128, 301, 2019 |
| 8 |
GMM clustering for heating load patterns in-depth identification and prediction model accuracy improvement of district heating system
Lu YK, Tian Z, Peng P, Niu JD, Li WC, Zhang HJ
Energy and Buildings, 190, 49, 2019 |
| 9 |
Constrained multimodal ensemble Kalman filter based on Kullback-Leibler (KL) divergence
Li RX, Jan NM, Huang B, Prasad V
Journal of Process Control, 79, 16, 2019 |
| 10 |
Gaussian process modelling with Gaussian mixture likelihood
Daemi A, Kodamana H, Huang B
Journal of Process Control, 81, 209, 2019 |
