Semi-supervised selective ensemble learning based on distance to model for nonlinear soft sensor development. - Weiming Shao; Xuemin Tian (Neurocomputing, 2017)

Adaptive Soft Sensor Development for Multi-Output Industrial Processes Based on Selective Ensemble Learning. - Weiming Shao; Sheng Chen 001; Chris J. Harris (IEEE Access, 2018)

Student's-t Mixture Regression-Based Robust Soft Sensor Development for Multimode Industrial Processes. - Jingbo Wang 004; Weiming Shao; Zhihuan Song (Sensors, 2018)

Nonlinear Inferential Sensor Development Based on GMM-ELM. - Weiming Shao; Zhiqiang Ge; Zhihuan Song; Li Zhao (ASCC, 2019)

Robust Soft Sensing for Multi-mode Processes Based on Bayesian Regularized Student's-t Mixture Regression. - Jingbo Wang 004; Weiming Shao; Zhihuan Song (ASCC, 2019)

Robust Supervised Probabilistic Factor Analysis and Its Application to Industrial Soft Sensor Modeling. - Weiming Shao; Hongwei Zhang; Zhihuan Song (IEEE Access, 2019)

Robust inferential sensor development based on variational Bayesian Student's-t mixture regression. - Jingbo Wang 004; Weiming Shao; Zhihuan Song (Neurocomputing, 2019)

Soft-Sensor Development for Processes With Multiple Operating Modes Based on Semisupervised Gaussian Mixture Regression. - Weiming Shao; Zhiqiang Ge; Zhihuan Song (IEEE Trans. Control. Syst. Technol., 2019)

Parallel Computing and SGD-Based DPMM For Soft Sensor Development With Large-Scale Semisupervised Data. - Weiming Shao; Le Yao; Zhiqiang Ge; Zhihuan Song (IEEE Trans. Ind. Electron., 2019)

An Efficient Modeling and Optimization Approach for Pressure Testing During Reentry Operation of Deepwater Drilling Riser System. - Kang Liu 006; Guoming Chen 002; Weiming Shao (IEEE Access, 2020)

Bayesian Nonlinear Gaussian Mixture Regression and its Application to Virtual Sensing for Multimode Industrial Processes. - Weiming Shao; Zhiqiang Ge; Le Yao; Zhihuan Song (IEEE Trans Autom. Sci. Eng., 2020)

Bayesian Just-in-Time Learning and Its Application to Industrial Soft Sensing. - Weiming Shao; Zhiqiang Ge; Zhihuan Song (IEEE Trans. Ind. Informatics, 2020)

Semisupervised Robust Modeling of Multimode Industrial Processes for Quality Variable Prediction Based on Student's t Mixture Model. - Weiming Shao; Zhiqiang Ge; Zhihuan Song; Jingbo Wang 004 (IEEE Trans. Ind. Informatics, 2020)

Semisupervised Bayesian Gaussian Mixture Models for Non-Gaussian Soft Sensor. - Weiming Shao; Zhiqiang Ge; Zhihuan Song (IEEE Trans. Cybern., 2021)

Dynamic Variational Bayesian Student's T Mixture Regression With Hidden Variables Propagation for Industrial Inferential Sensor Development. - Jingbo Wang 004; Weiming Shao; Xinmin Zhang; Zhihuan Song (IEEE Trans. Ind. Informatics, 2021)

Virtual Sensor Development for Multioutput Nonlinear Processes Based on Bilinear Neighborhood Preserving Regression Model With Localized Construction. - Chihang Wei; Weiming Shao; Zhihuan Song (IEEE Trans. Ind. Informatics, 2021)

Hierarchical Quality Monitoring for Large-Scale Industrial Plants With Big Process Data. - Le Yao; Weiming Shao; Zhiqiang Ge (IEEE Trans. Neural Networks Learn. Syst., 2021)

Cumulative dual-branch network framework for long-tailed multi-class classification. - Saite Fan; Xinmin Zhang; Zhihuan Song; Weiming Shao (Eng. Appl. Artif. Intell., 2022)

Block-Wise Parallel Semisupervised Linear Dynamical System for Massive and Inconsecutive Time-Series Data With Application to Soft Sensing. - Weiming Shao; Yougao Li; Wenxue Han; Dongya Zhao (IEEE Trans. Instrum. Meas., 2022)

Research and Development of a Multi-State Non-Invasive Monitoring System for Cluster Motors. - Zhisheng Lv; Delin Chen; Weiming Shao (IECON, 2023)

A novel semi-supervised robust learning framework for dynamic generative latent variable models and its application to industrial virtual metrology. - Wenxue Han; Weiming Shao; Chihang Wei; Wei Song; Can Chen; Junghui Chen (Adv. Eng. Informatics, 2024)

A mixture of shallow neural networks for virtual sensing: Could perform better than deep neural networks. - Weiming Shao; Xu Li; Yupeng Xing; Junghui Chen (Expert Syst. Appl., 2024)

Virtual Sensing of Key Variables in the Hydrogen Production Process: A Comparative Study of Data-Driven Models. - Yating Yao; Yupeng Xing; Ziteng Zuo; Chihang Wei; Weiming Shao (Sensors, 2024)

Semi-Supervised Robust Hidden Markov Regression for Large-Scale Time-Series Industrial Data Analytics and its Applications to Soft Sensing. - Weiming Shao; Wenxue Han; Chuanfa Xiao; Lei Chen; Meng-Qin Yu; Junghui Chen (IEEE Trans Autom. Sci. Eng., 2025)

Multi-strategy improved black-winged kite algorithm and its application in short-term load forecasting using gated recurrent unit neural networks. - Hao Zhang; Liming Liu; Yongkuan Yang; Weiming Shao (Evol. Intell., 2025)

A physical causality-informed generative latent variable modeling paradigm for industrial virtual metrology. - Weiming Shao; Hongjian Yu; Wenxue Han; Zeyu Yang; Junghui Chen (Adv. Eng. Informatics, 2026)