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Weiming Shao
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Year
Adaptive soft sensor for quality prediction of chemical processes based on selective ensemble of local partial least squares models
W Shao, X Tian
Chemical Engineering Research and Design 95, 113-132, 2015
1202015
Online soft sensor design using local partial least squares models with adaptive process state partition
W Shao, X Tian, P Wang, X Deng, S Chen
Chemometrics and Intelligent Laboratory Systems 144, 108-121, 2015
562015
Semi-supervised selective ensemble learning based on distance to model for nonlinear soft sensor development
W Shao, X Tian
Neurocomputing 222, 91-104, 2017
542017
Quality variable prediction for chemical processes based on semisupervised Dirichlet process mixture of Gaussians
W Shao, Z Ge, Z Song
Chemical Engineering Science 193, 394-410, 2019
402019
Soft-sensor development for processes with multiple operating modes based on semisupervised Gaussian mixture regression
W Shao, Z Ge, Z Song
IEEE Transactions on Control Systems Technology 27 (5), 2169-2181, 2018
362018
Parallel computing and SGD-based DPMM for soft sensor development with large-scale semisupervised data
W Shao, L Yao, Z Ge, Z Song
IEEE Transactions on Industrial Electronics 66 (8), 6362-6373, 2018
342018
Nonlinear industrial soft sensor development based on semi-supervised probabilistic mixture of extreme learning machines
W Shao, Z Ge, Z Song, K Wang
Control Engineering Practice 91, 104098, 2019
322019
Local partial least squares based online soft sensing method for multi-output processes with adaptive process states division
W Shao, X Tian, P Wang
Chinese Journal of Chemical Engineering 22 (7), 828-836, 2014
272014
Semisupervised Robust Modeling of Multimode Industrial Processes for Quality Variable Prediction Based on Student's t Mixture Model
W Shao, Z Ge, Z Song, J Wang
IEEE Transactions on Industrial Informatics 16 (5), 2965-2976, 2019
252019
Supervised local and non-local structure preserving projections with application to just-in-time learning for adaptive soft sensor
W Shao, X Tian, P Wang
Chinese Journal of Chemical Engineering 23 (12), 1925-1934, 2015
222015
Bayesian just-in-time learning and its application to industrial soft sensing
W Shao, Z Ge, Z Song
IEEE Transactions on Industrial Informatics 16 (4), 2787-2798, 2019
192019
Semi-supervised mixture of latent factor analysis models with application to online key variable estimation
W Shao, Z Ge, Z Song
Control Engineering Practice 84, 32-47, 2019
192019
Adaptive soft sensor development for multi-output industrial processes based on selective ensemble learning
W Shao, S Chen, CJ Harris
IEEE Access 6, 55628-55642, 2018
182018
Plastic bag model of the artificial gas lift system for slug flow analysis
W Shao, I Boiko, A Al-Durra
Journal of Natural Gas Science and Engineering 33, 573-586, 2016
172016
Control-oriented modeling of gas-lift system and analysis of casing-heading instability
W Shao, I Boiko, A Al-Durra
Journal of Natural Gas Science and Engineering 29, 365-381, 2016
152016
Semisupervised Bayesian Gaussian mixture models for non-Gaussian soft sensor
W Shao, Z Ge, Z Song
IEEE Transactions on Cybernetics 51 (7), 3455-3468, 2019
122019
Soft sensor development for nonlinear and time‐varying processes based on supervised ensemble learning with improved process state partition
W Shao, X Tian, P Wang
Asia‐Pacific Journal of Chemical Engineering 10 (2), 282-296, 2015
122015
Bayesian nonlinear Gaussian mixture regression and its application to virtual sensing for multimode industrial processes
W Shao, Z Ge, L Yao, Z Song
IEEE Transactions on Automation Science and Engineering 17 (2), 871-885, 2019
112019
Semi-supervised variational Bayesian Student’st mixture regression and robust inferential sensor application
J Wang, W Shao, Z Song
Control Engineering Practice 92, 104155, 2019
102019
Autoencoder-based nonlinear Bayesian locally weighted regression for soft sensor development
K Liu, W Shao, G Chen
ISA transactions 103, 143-155, 2020
92020
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