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Slow feature analysis for monitoring and diagnosis of control performance

Journal of process control, 2016-03, Vol.39, p.21-34

2016

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Online temperature estimation of Shell coal gasification process based on extended Kalman filter

Chinese journal of chemical engineering, 2022-07, Vol.47 (7), p.134-144

2022

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Deep learning technique for process fault detection and diagnosis in the presence of incomplete data

Chinese journal of chemical engineering, 2020-09, Vol.28 (9), p.2358-2367

2020

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A review of control loop monitoring and diagnosis:Prospects of controller maintenance in big data era

Chinese journal of chemical engineering, 2016-08, Vol.24 (8), p.952-962

2016

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A Novel Two-Level Optimization Framework Based on Constrained Ordinal Optimization and Evolutionary Algorithms for Scheduling of Multipipeline Crude Oil Blending

Industrial & engineering chemistry research, 2012-07, Vol.51 (26), p.9078-9093

2012

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Recursive Slow Feature Analysis for Adaptive Monitoring of Industrial Processes

IEEE transactions on industrial electronics (1982), 2018-11, Vol.65 (11), p.8895-8905

2018

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Data-driven soft sensor development based on deep learning technique

Journal of process control, 2014-03, Vol.24 (3), p.223-233

2014

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Trajectory Planning for Automated Driving Based on Ordinal Optimization

Tsinghua science and technology, 2017-02, Vol.22 (1), p.62-72

2017

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A continuous-time formulation for refinery production scheduling problems involving operational transitions in mode switching

Chinese journal of chemical engineering, 2016-08, Vol.24 (8), p.1020-1031

2016

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Adaptive Nonlinear Model Predictive Control Using an On-line Support Vector Regression Updating Strategy

Chinese journal of chemical engineering, 2014-07, Vol.22 (7), p.774-781

2014

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Simultaneous Identification of Bidirectional Path Models Based on Process Data

IEEE transactions on automation science and engineering, 2015-04, Vol.12 (2), p.666-679

2015

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Multiple kernel learning-aided robust optimization: Learning algorithm, computational tractability, and usage in multi-stage decision-making

European journal of operational research, 2021-08, Vol.292 (3), p.1004-1018

2021

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A novel two-stage Lagrangian decomposition approach for refinery production scheduling with operational transitions in mode switching

Chinese journal of chemical engineering, 2015-11, Vol.23 (11), p.1793-1800

2015

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Probabilistic slow feature analysis-based representation learning from massive process data for soft sensor modeling

AIChE journal, 2015-12, Vol.61 (12), p.4126-4139

2015

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A novel white component analysis for dynamic process monitoring

Journal of process control, 2023-07, Vol.127, p.102998, Article 102998

2023

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A Holistic Probabilistic Framework for Monitoring Nonstationary Dynamic Industrial Processes

IEEE transactions on control systems technology, 2021-09, Vol.29 (5), p.2239-2246

2021

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Data-driven output prediction and control of stochastic systems: An innovation-based approach

Automatica (Oxford), 2025-01, Vol.171, p.111897, Article 111897

2025

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Dynamic Soft Sensor Development Based on Convolutional Neural Networks

Industrial & engineering chemistry research, 2019-07, Vol.58 (26), p.11521-11531

2019

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Generalized grouped contributions for hierarchical fault diagnosis with group Lasso

Control engineering practice, 2019-12, Vol.93, p.104193, Article 104193

2019

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Efficient low-order system identification from low-quality step response data with rank-constrained optimization

Control engineering practice, 2021-02, Vol.107, p.104671, Article 104671

2021

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Inventory pinch analysis based bi-level heuristic algorithm for scheduling of the PVC production by calcium carbide method

2016 35th Chinese Control Conference (CCC), 2016, p.2678-2684

2016

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Efficient Relay Autotuner of Industrial Controllers via Rank-Constrained Identification of Low-Order Time-Delay Models

IEEE transactions on control systems technology, 2023-07, Vol.31 (4), p.1787-1802

2023

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Operation optimization of Shell coal gasification process based on convolutional neural network models

Applied energy, 2021-06, Vol.292, p.116847, Article 116847

2021

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Group-sparsity-enforcing fault discrimination and estimation with dynamic process data

Journal of process control, 2021-09, Vol.105, p.236-249

2021

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Improved Hybrid Differential Evolution-Estimation of Distribution Algorithm with Feasibility Rules for NLP/MINLP Engineering Optimization Problems

Chinese journal of chemical engineering, 2012-12, Vol.20 (6), p.1074-1080

摆亮王钧炎江永亨黄德先

2012

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Slow feature analysis for monitoring and diagnosis of control performance

Online temperature estimation of Shell coal gasification process based on extended Kalman filter

Deep learning technique for process fault detection and diagnosis in the presence of incomplete data

A review of control loop monitoring and diagnosis:Prospects of controller maintenance in big data era

A Novel Two-Level Optimization Framework Based on Constrained Ordinal Optimization and Evolutionary Algorithms for Scheduling of Multipipeline Crude Oil Blending

Recursive Slow Feature Analysis for Adaptive Monitoring of Industrial Processes

Data-driven soft sensor development based on deep learning technique

Trajectory Planning for Automated Driving Based on Ordinal Optimization

A continuous-time formulation for refinery production scheduling problems involving operational transitions in mode switching

Adaptive Nonlinear Model Predictive Control Using an On-line Support Vector Regression Updating Strategy

Simultaneous Identification of Bidirectional Path Models Based on Process Data

Multiple kernel learning-aided robust optimization: Learning algorithm, computational tractability, and usage in multi-stage decision-making

A novel two-stage Lagrangian decomposition approach for refinery production scheduling with operational transitions in mode switching

Probabilistic slow feature analysis-based representation learning from massive process data for soft sensor modeling

A novel white component analysis for dynamic process monitoring

A Holistic Probabilistic Framework for Monitoring Nonstationary Dynamic Industrial Processes

Data-driven output prediction and control of stochastic systems: An innovation-based approach

Dynamic Soft Sensor Development Based on Convolutional Neural Networks

Generalized grouped contributions for hierarchical fault diagnosis with group Lasso

Efficient low-order system identification from low-quality step response data with rank-constrained optimization

Inventory pinch analysis based bi-level heuristic algorithm for scheduling of the PVC production by calcium carbide method

Efficient Relay Autotuner of Industrial Controllers via Rank-Constrained Identification of Low-Order Time-Delay Models

Operation optimization of Shell coal gasification process based on convolutional neural network models

Group-sparsity-enforcing fault discrimination and estimation with dynamic process data

Improved Hybrid Differential Evolution-Estimation of Distribution Algorithm with Feasibility Rules for NLP/MINLP Engineering Optimization Problems

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