Paper Citation Report (引用報告) (ResearcherID
                     Paper Citation Report (引用報告) (Google Scholar Profile)

 

         

  • S. Gu, J. Chen, and L. Xie, Automatic Segmentation of Batch Processes into Multi-Local State-Space Models for Fault Detection, Chem. Eng. Sci., 2022.(Accepted).

  • R. Lin, J. Chen, L. Xie and H. Su, Accelerating Reinforcement Learning with Case-based Model-assisted Experience Augmentation for Process Control, Neural Networks, 2022.(Accepted).

  • Y.-S. Lee and J. Chen, Developing Semi-Supervised Latent Dynamic Variational Autoencoders to Enhance Prediction Performance of Product Quality,Chem. Eng. Sci., 2022.(Accepted).

  • G. Mu, J. Chen, J. Liu, W. Shao and D. Zhao, State Prediction of Distributed Parameter Systems Based on Multi-Source Spatiotemporal Information,  J. Process Contr.,  2022.(Accepted).

  • K. Wang, J. Chen, Z. Song, Y. Wang and C. Yang, Deep Neural Network Embedded Stochastic Nonlinear State Space Models and their Applications to Process Monitoring, IEEE Trans Neural Netw Learn Syst2021.(Accepted)

  • G. Mu, T. Liu, J. Chen, J. Zhang and C. Zhong, Variational PLS based Calibration Model Building with Semi-supervised Learning for Moisture Measurement during Fluidized Bed Drying by NIR Spectroscopy,  IEEE Trans. Instrum. Meas., 71, 1006713, 2022.

  • J. Liu, D. Sun, Y. Xiao, and J. Chen, Developing Tensor-based Common and Special Feature Analysis for Comprehensive Monitoring of Complex Batch Processes, Ind. Eng. Chem. Res., 61(28), 10156-10171, 2022.

  • Y.-S. Lee and J. Chen, Using Source Data to Aid and Build Variational State-Space Autoencoders with Sparse Target Data for Process Monitoring Learning Systems, Neural Networks,  154, 455-468, 2022.

  • X. Wu, N. Zhang, L. Xie, W. Ci, J. Chen, and S. Lu, Thermo-economic Optimization Design of the ORC System In-stalled on a Light-Duty Vehicle for Waste Heat Recovery from Exhaust Heat, Energies, 15(12), 4486, 2022.

  • M. Ren, W. Zhang, J. Chen, P. Shi and G. Yan, Performance Assessment for Non-Gaussian Systems by Minimum Entropy Control and Dynamic Data Reconciliation, J. Franklin Inst., 359, 3930-3950, 2022.

  • L.-X. You and J. Chen, Auto-Generated Multi-Local PLS Models without Pre-classified for Quality Monitoring of Nonlinear Processes with Unevenly Distributed Data, Ind. Eng. Chem. Res., 61(17), 5898-5913, 2022.

  • J. Liu, D. Sun, and J. Chen, Comparative Study on Wavelet Functional Partial Least Squares Soft Sensor for Complex Batch Processes, Chem. Eng. Sci.,  254, 117601, 2022.

  • Mu, T. and J. Chen, Developing a Conditional Variational Autoencoder to Guide Spectral Data Augmentation for Calibration Modeling,  IEEE Trans. Instrum. Meas., 17, 2501008, 2022.

  • Y. Zhang, Y.-S. Lee, H. Lin, and J. Chen, Establishing Convolutional Neural Network Kalman Recurrent Variational Autoencoder Using Infrared Imaging for Process Monitoring: An Application in Spinning Disc Processes  IEEE Trans. Instrum. Meas., 71, 5001712, 2022.

  • J. Liu, G.-Y. Hou, and J. Chen, A Supervised Functional Modeling Method for Long Durations of Batch Processes with Limited Batch Data, Chem. Eng. Sci.,  247, 116991, 2022.

  • Y.-S. Lee and J. Chen, Augmenting Deviation of Faults from the Normal Using Fault Assistant Gaussian Mixture Prior Variational Autoencoder, J .Taiwan Inst. Chem. Eng., 130, 103921, 2022. 

  • G. Hu, Z. Zhang, J. Chen, Z. Zhang, A. Armaou, Elman Neural Networks Combined with Extended Kalman Filters for Data-driven Dynamic Data Reconciliation in Nonlinear Dynamic Process Systems, Ind. Eng. Chem. Res., 60(42), 15219-15235, 2021.

  • W. Zhu, Z. Zhang, J. Chen, S. Zhao and S Huang, Dynamic Data Reconciliation to Enhance the Performance of Feedforward/Feedback Control Systems with Measurement Noise,  J. Process Contr., 108, 12-24, 2021.

  • L. L. T. Chan and J. Chen, Gaussian Process Model Based Multi-Source Labeled Data Transfer Learning for Reducing Cost of Modeling Target Chemical Processes with Unlabeled Data, Control Eng. Pract,,  117, 104941, 2021.

  • Q. Chen, J. Chen, X. Lung, L. Xie, N. ur Rehman and H. Su, Self-tuning Variational Mode Decomposition, J. Franklin Inst., 358 (15), 7825-7862, 2021.

  • J. Liu, J. Hou and J. Chen, Dual-layer Feature Extraction Based Soft Sensor Methods and Applications to Industrial Polyethylene Processes, Comput. Chem. Eng., 154, 107469, 2021.

  • X. Wu, J. Chen, L. Xie, Y.-S. Lee, C.-I Chen and H. Su, Application of Convolutional Neural Networks for Multi-Stage Semiconductor Processes, J. Chem. Eng. Japan, 54, 449-455, 2021

  • Y. Lyu, J. Chen, Z. Song and Q. Zhang, Synthesizing Data by Transferring Information in Data-intensive Regions to Enhance Process Monitoring Performance in Data-scarce Region, Can. J. Chem. Eng. 99(S1), S521-S539, 2021.

  • S. K. Ooi, D. Tanny, J. Chen, and K. Wang, Developing Semi-supervised Variational Autoencoder-Generative Adversarial Network Models to Enhance Quality Prediction Performance, Chemometer Intell. Lab., 217, 104385, 2021.

  • Y. Lyu, J. Chen, and Z. Song, Synthesizing Labeled Data to Enhance Soft Sensor Performance in Data-scarce Regions, Control Eng. Pract,  115, 104903, 2021. 

  • L.-X. You and J. Chen, A Variable Relevant Multi-Local PCA Modeling Scheme to Monitor a Nonlinear Chemical Process, Chem. Eng. Sci., 246, 116851, 2021.

  • L. Zhu, Z. Li and J. Chen, Evaluating and Predicting Energy Efficiency Using Slow Feature Partial Least Squares Method for Large-scale Chemical Plants, Energy, 230, 120582, 2021. 

  • Z. Li, Y.-S. Lee, J. Chen and Y. Qian, Variable Moving Window PLS Models for Long-term NOx Emission Prediction of Coal-fired Power Plants, Fuel, 296, 120441, 2021.

  • M. Ren, J. Chen, P. Shi and G. Yan, Statistical Information Based Two-Layer Model Predictive Control with Dynamic Economy and Control Performance for Non-Gaussian Stochastic Process, J. Franklin Inst., 358, 2279-2300, 2021.

  • G. Mu, T. Liu, C. Xue and J. Chen, Semi-Supervised Learning based Calibration Model Building of NIR spectroscopy for In-Situ Measurement of Biochemical Processes under Insufficiently and Inaccurately Labeled Sample, IEEE Trans. Instrum. Meas. 70, 2509912, 2021.

  • J. Liu, J. Chen, and D. Wang, Global-local Based Wavelet Functional Principal Component Analysis for Fault Detection and Diagnosis in Batch Processes, Chemometer Intell. Lab. 212, 104279, 2021.

  • J. Liu, J. Chen, and D. Wang, Linear and Exponential Fault-assistant Feature Extraction Methods for Process Monitoring, Control Eng. Pract, 109, 104732, 2021.

  • K. Wang, X. Yuan, J. Chen and Y. Wang Supervised and Semi-supervised Probabilistic Learning with Deep Neural Networks for Concurrent Process-Quality Monitoring, Neural Networks, 136, 54-62, 2021.

  • Y.-S. Lee and J. Chen, Enhancing Monitoring Performance of Data Sparse Nonlinear Processes through Information Sharing among Different Grades Using Gaussian Mixture Prior Variational Autoencoders, Chemometer Intell. Lab., 208, 104219, 2021.

  • J. Liu, T. Liu, J. Chen, H. Yu, F. Zhang and F. Sun, Data-driven modelling of product crystal size distribution and optimal input design for batch cooling crystallization processes, J. Process Contr., 96, 1-14, 2020.

  • K. Wang, B. Gopaluni, J. Chen and Z. Song, Deep Learning of Complex Batch Process Data and Its Application on Quality Prediction, IEEE Trans. on Industrial Informatics,  16(12), 7233-7242, 2020.

  • J. Liu, D. Wang, J. Chen and J. Hou, Functional Soft Sensor Based on Spectra Data for Predicting Multiple Quality Variables, IEEE  Access,  8, 160355-160362, 2020.

  • Z. Hong, L. Xu and J. Chen, Artificial Evolution Based Cost-reference Particle Filter for Nonlinear State and Parameter Estimation in Process Systems with Unknown Noise Statistics and Model Parameters, J .Taiwan Inst. Chem. Eng., 112, 377-387, 2020.

  • Z. Hong, L. Xu and J. Chen, Particle Filter Combined with Data Reconciliation for Nonlinear State Estimation with Unknown Initial Conditions in Nonlinear Dynamic Process Systems, ISA Transactions, 103, 203-214, 2020.

  • X. Wu, J. Chen and L. Xie, Optimal Design of Organic Rankine Cycles for Exhaust Heat Recovery from Light-Duty Vehicles in View of Various Exhaust Gas Conditions and Negative Aspects of Mobile Vehicles, Applied Thermal Engineering, 179, 115645, 2020.

  • J. Liu, T. Liu, G. Mu and J. Chen, Wavelet Based Calibration Model Building of NIR Spectroscopy for In-situ Measurement of Granule Moisture Content during Fluidized Bed Drying,  Chem. Eng. Sci., 226, 115867, 2020.

  • J. Liu, D. Wang and J. Chen, Novel Monitoring Framework Based on Generalized Tensor PCA for 3-Dimensional Batch Process Data,  Ind. Eng. Chem. Res., 59, 10493-10508, 2020.

  • K. Wang, J. Chen, L. Xie and H. Su, Transfer Learning Based on Incorporating Source Knowledge Using Gaussian Process Models for Quick Modeling of Dynamic Target Processes, Chemometer Intell. Lab.,  198, 103911, 2020. 

  • Q. Chen, J. Chen, X. Lang, L. Xie, S. Lu and H. Su, Detection and Diagnosis of Oscillations in Process Control by Fast Adaptive Chirp Mode Decomposition, Control Eng. Pract,,  97, 104307, 2020. 

  • J. Liu, J. Chen and D. Wang, Wavelet Functional Principal Component Analysis for Batch Process Monitoring, Chemometer Intell. Lab., 196, 103897, 2020.

  • K. Wang, J. Chen and Z. Song, A Sparse Loading-based Contribution Method for Multivariate Control Performance Diagnosis, J. Process Contr.,  85, 199-213, 2020. 

  • X. Wu, J. Chen, L. Xie, L. L. T. Chan  and C.-I. Chen, Development of Convolutional Neural Network Based Gaussian Process Regression to Construct a Novel Probabilistic Virtual Metrology in Multi-Stage Semiconductor Processes, Control Eng. Pract, 96, 104262, 2020.

  • Z. Zhang, L. L. T. Chan, J. Chen and Z. Shao, Correntropy Based Data Reconciliation and Gross Error Detection for Bilinear Systems, Chem. Eng. Sci., 212, 115327, 2020.

  • Z. Zhang and J. Chen, Enhancing Performance of Generalized Minimum Variance Control via Dynamic Data Reconciliation, J. Franklin Inst., 356(15) 8829-8854, 2019.

  • G. Mu, T. Liu, J. Chen, L. Xia and X. Yu, 110th Anniversary: Real-Time Endpoint Detection of Fluidized Bed Drying Process Based on a Switching Model of Near-Infrared Spectroscopy,  Ind. Eng. Chem. Res., (58) 16777-16786, 2019.

  • K. Wang, L. Rippon, J. Chen, Z. Song, and B. Gopaluni, Data-Driven Dynamic Modeling and Online Monitoring for Multiphase and Multimode Batch Processes with Uneven Batch Durations, Ind. Eng. Chem. Res., (58) 13628-13641, 2019. 

  • K. Wang, J. Chen, L. Xie and H. Su, Decision Making Scheme of Integration Design and Control under Uncertainty for Enhancing the Economic Performance of Chemical Processes with Multiplicity Behaviors, Chem. Eng. Res. Des., (150) 327-340, 2019.

  • K. Wang, J. Chen, and Z. Song, Concurrent Fault Detection and Anomaly Location in Closed-Loop Dynamic Systems with Measured Disturbances, IEEE Trans. Autom. Sci. Eng., 16(3), 1033-1045, 2019.

  • X. Wu, J. Chen, and L. Xie, Fast Economic Nonlinear Model Predictive Control Strategy of Organic Rankine Cycle for Waste Heat Recovery: Simulation-Based Studies, Energy, 180, 520-534, 2019.

  • L. Zhu and J. Chen, Energy Efficiency Evaluation and Prediction of Large-Scale Chemical Plants Using Partial Least Squares Analysis Integrated with Gaussian Process Models, Energy Conversion and Management, 195, 690-700, 2019. 

  • L. Zhu and J. Chen, Development of Energy Efficiency Principal Component Analysis Model for Factor Extraction and Efficiency Evaluation in Large-scale Chemical Processes, International Journal of Energy Research, 43, 814-828, 2019. 

  • Y. Lyu, J. Chen, and Z. Song, Image-Based Process Monitoring Using Deep Learning Framework, Chemometer Intell. Lab., 189, 8-17, 2019.

  • K. Wang, J. Chen and Z. Song, Using Multivariate Pattern Segmentation to Assess Process Performance and Mine Good Operation Conditions for Dynamic Chemical Industry,  Chem. Eng. Sci.,  201, 339-348, 2019.

  • P. Lu, J. Chen and L. Xie, Disturbance-Based Alternate Feedback Control Scheme to Enhance Economic Performance of Batch Processes, Ind. Eng. Chem. Res., 58, 4143-4153, 2019.

  • K. Wang, M. G. Forbes, B. Gopaluni, J. Chen and Z. Song, Systematic Development of a New Variational Autoencoder Model Based on Uncertain Data for Monitoring Nonlinear Processes, IEEE  Access,  7(1) 22554-22565, 2019. 

  • L. Zhou, J. Chen, J. Jie and Z. Song, Multiple Probability Principal Component Analysis for Process Monitoring with Multi-Rate Measurements, J .Taiwan Inst. Chem. Eng., 96, 18-28, 2019. 

  • Z. Zhang and J. Chen, Fault Detection and Diagnosis Based on Particle Filters Combined with Interactive Multiple-Model Estimation in Dynamic Process Systems, ISA Transactions,  85, 247-261, 2019.

  • C. Wei, J. Chen, Z. Song and C.-I. Chen, Development of Self-Learning Kernel Regression Models for Virtual Sensors on Nonlinear Processes, IEEE Trans. Autom. Sci. Eng.,  16(1) 286-297, 2019. 

  • L. Zhu and J. Chen, A Dynamic Approach to Energy Efficiency Estimation in the Large-Scale Chemical Plant, Journal of Cleaner Production, 212, 1072-1085, 2019. 

  • K. Wang, J. Chen and Z. Song, Performance Analysis of Dynamic PCA for Closed Loop Process Monitoring and Its Improvement by Output Oversampling Scheme, IEEE Trans. Control Syst. Technol., 27(1) 378-385, 2019.

  • C. Wei, J. Chen, Z. Song and C.-I. Chen, Adaptive Virtual Sensors Using SNPER for the Localized Construction and Elastic Net Regularization in Nonlinear Processes, Control Eng. Pract., 83, 129-140, 2019

  • K. Wang, J. Chen and Z. Song, A New Excitation Scheme for Closed-loop Subspace Identification Using Additional Sampling Outputs and its Extension to Instrumental Variable Method, J. Franklin Inst., 355, 6675-6692, 2018. 

  • X. Wu, J. Chen and L. Xie, Integrated Operation Design and Control of Organic Rankine Cycle Systems with Disturbances, Energy, 163,115-129, 2018.

  • L. L. T. Chan and J. Chen, Improving the Energy Cost of an Absorber-Stripper CO2 Capture Process through Economic Model Predictive Control, International Journal of Greenhouse Gas Control., 76, 158-166, 2018.

  • K. Wang, J. Chen and Z. Song, Fault Diagnosis for Processes with Feedback Control Loops by Shifted Output Sampling Approach, J. Franklin Inst., 355 (7), 3249-3273, 2018.

  • J. Liu, T. Liu and J. Chen, Quality Prediction for Multi-grade Processes by Just-in-time Latent Variable Modeling with Integration of Common and Special Features,  Chem. Eng. Sci., 191, 31-41, 2018.

  • L. L. T. Chan and J. Chen, Economic Model Predictive Control of Distillation Startup Based on Probabilistic Approach, Chem. Eng. Sci., 186, 26-35, 2018.

  • C. Wei, J. Chen and Z. Song, Multilevel MVU Models with Localized Construction for Monitoring Processes with Large Scale Data, J. Process Contr.,  67, 176-196, 2018. 

  • L. L. T. Chan, X. Wu, J. Chen, L. Xie and C.-I. Chen, Just-In-Time Modeling with Variable Shrinkage Based on Gaussian Processes for Semiconductor Manufacturing, IEEE Trans. Semicond. Manuf., 31(3) 1-8, 2018.

  • X. Feng, D. Li, J. Chen, M. Niuc, X. Liu, L. L. T. Chan and W. Li, Kinetic Parameter Estimation and Simulation of Trickle-bed Reactor for Hydrodesulfurization of Whole Fraction Low-Temperature Coal Tar, Fuel, 230 113-125, 2018.

  • J. Liu, T. Liu, J. Chen and P. Qin, Novel Common and Special Feature Extraction for Monitoring Multi-grade Processes Journal of Process Control,  J. Process Contr., 66, 98-107, 2018.

  • L. Zhou, J. Chen, B. Hou and Z. Song, Multi-Grade Principal Component Analysis for Fault Detection with Multiple Production Grades,  Chemometer Intell. Lab., 175, 20-29, 2018. 

  • L. L. T. Chan, Q.-Y. Wu and J. Chen, Dynamic Soft Sensors with Active Forward-Update Learning for Selection of Useful Data from Historical Big Database,  Chemometer Intell. Lab., 175, 87-103, 2018.

  • P. Lu, J. Chen and L. Xie, ILC Based Economic Optimization for Batch Processes Using Helpful Disturbance Information, Ind. Eng. Chem. Res. 57(10), 3717-3731, 2018.

  • J. Liu, T. Liu and J. Chen, Sequential Local-based Gaussian Mixture Model for Monitoring Multiphase Batch Processes,  Chem. Eng. Sci., 181, 101-113, 2018. 

  • L. Zhu and J. Chen, Prognostics of PEM Fuel Cells Based on Gaussian Process State Space Models, Energy, 149, 63-73, 2018. 

  • L. L. T. Chan and J. Chen, Melt Index Prediction Using Mixture of Gaussian Process Regression with Embedded Clustering and Variable Selections,  Journal of Applied Polymer Science, 134,  45237, 2017. 

  • L. L. T. Chan and J. Chen, Probabilistic Uncertainty Based Simultaneous Process Design and Control with Iterative Expected Improvement Model,  Comput. Chem. Eng., 106, 609-620, 2017. 

  • Y. Liu, Y. Fan and J. Chen, Flame Images for Oxygen Content Prediction of Combustion Systems Using DBN, Energy & Fuels,  31 (8), 8776-8783, 2017. 

  • Y. Liu, Q.-Y. Wu and J. Chen Active Selection of Informative Data for Sequential Quality Enhancement of Soft Sensor Models with Latent Variables, Ind. Eng. Chem. Res., 56 (16), 4804–4817, 2017.

  • Z. Zhu, Z. Meng, Z. Zhang, J. Chen and Y. Dai, Robust Particle Filter for State Estimation Using Measurements with Different Types of Gross Errors, ISA Transactions, 69, 281-295, 2017.

  • L. Jiang, Z. Song, Z. Ge and J. Chen, Robust Self-supervised Model and Its Application for Fault Detection, Ind. Eng. Chem. Res., 56(26), 7503–7515, 2017.

  • J. Chen and S.-W. Gu, Development of LTV Subspace System Identification Using Basis Functions Approach to Assessing the Performance of Control Loops for Nonlinear Processes, J .Taiwan Inst. Chem. Eng., 73, 123-134, 2017.

  • K. Wang, J. Chen and Z. Song, Data-Driven Sensor Fault Diagnosis Systems for Linear Feedback Control Loops, J. Process Contr., 54, 152-171, 2017.

  • L. L. T. Chan, C.-P. Chou and J. Chen, Hybrid Model Based Expected Improvement Control for Cyclical Operations of Microfiltration Membrane Processes,  Chem. Eng. Sci., 166, 77-90, 2017.

  • Z. Zhang, Y.-Y. Chuang and J. Chen, Using Clustering Based Logical Equation Set to Decompose Large Scale Chemical Processes for Parallel Solving Data Reconciliation and Parameter Estimation Problem, Chem. Eng. Res. Des., 120, 396-409, 2017.

  • J. Zhang, M. Lin, J. Chen, J. Xu and K. Li, PLS-based multi-loop robust H2 control for improvement of operating efficiency of waste heat energy conversion systems with organic Rankine cycle, Energy, 123, 460-472, 2017.

  • Z. Yan, J. Chen and Z. Zhang, Using Hidden Markov Model to Identify Oscillation Temporal Pattern for Control Loops, Chem. Eng. Res. Des., 119, 117-129, 2017.

  • L. Zhou, J. Chen, L. Yao, Z. Song and B. Hou, Similarity Based Robust Probability Latent Variable Regression Model and its Kernel Extension for Process Monitoring, Chemometer Intell. Lab., 161, 88-95, 2017.

  • Z. Zhang and J. Chen , Dynamic Data Reconciliation for Enhancing Performance of Minimum Variance Control in Univariate and Multivariate Systems, Ind. Eng. Chem. Res., 55(41), 10990-11002, 2016.

  • C. Wei, J. Chen and Z. Song, Developments of Two Supervised Maximum Variance Unfolding Algorithms for Process Classification, Chemometer Intell Lab., 159, 31-44, 2016.

  • L. Xie, X. Cai, J. Chen and H. Su, GA Based Decomposition of Large Scale Distributed Model Predictive Control System, Control Eng. Pract., 57, 111-125, 2016.

  • M. Ren, T. Cheng, J. Chen, X. Xu and L. Cheng, Single Neuron Stochastic Predictive PID Control Algorithm for Nonlinear and Non-Gaussian Systems Using the Survival Information Potential Criterion, Entropy, 18, 218, 2016

  • Y. Liu, C.-P. Chou, J. Chen and J.-Y. Lai, Active Learning Assisted Strategy of Constructing Hybrid Models in Repetitive Operations of Membrane Filtration Processes: Using Case of Mixture of Bentonite Clay and Sodium Alginatel,  J. Membr. Sci. 515, 245-257, 2016

  • L. L. T. Chan, T. Chen and J. Chen, PID Based Nonlinear Processes Control Model Uncertainty Improvement by Using Gaussian Process Model, J. Process Contr., 42, 77-89, 2016.

  • L. Xie, X. Lang, J. Chen, A. Horch and H. Su, Time-varying Oscillation Detector Based on Improved LMD and Robust Lempel-Ziv Complexity, Control Eng. Pract,, 51, 48-57, 2016.

  • Z. Yan and J. Chen, Enhancing Quality of Statistic Monitoring Models by Training Set Design with Active Learning Approach, Chemometer Intell Lab., 151, 201-218, 2016.

  • Z.-Q. Ge and J. Chen, Plant-Wide Industrial Process Monitoring: A Distributed Modeling Framework, IEEE Trans. Ind. Informat.12(1), 310-312, 2016.

  • J. Zhang, L.-Y. Zhang, J. Chen, J. Xu and K. Li, Performance Assessment of Cascade Control Loops with Non-Gaussian Disturbances Using Entropy Information, Chem. Eng. Res. Des.104, 68-90, 2015.

  • Y. Liu, Z. Zhang and J. ChenEnsemble Local Kernel Learning for Online Prediction of Distributed Product Outputs in Chemical Processes, Chem. Eng. Sci., 137, 140-151, 2015. 

  • Z. Zhang, Z. Shao and J. ChenProgramming Strategies of Sequential Incremental-Scale Sub-problems for Large Scale Data Reconciliation and Parameter Estimation with Multi-Operational Conditions, Ind. Eng. Chem. Res., 54(21) 5697-5709, 2015.

  • P. Sun, L. Xie and J. ChenSpatial Batch Optimal Design Based on Self-Learning Gaussian Process Models for LPCVD Processes, Chinese Journal of Chemical Engineering., 23(12), 1958–1964, December 2015.

  • P.-P. Oh, M.-F. Chong, H. L. N. Lau, Y.-M. Choo and J. Chen, Modelling of a Membrane Reactor System for Crude Palm Oil Transesterification. Part I: Chemical And Phase Equilibrium, AIChE Journal,  61(6) 1968-1980, 2015.

  • J. Zhang, M.-M. Lin, J. Chen, K. Li and J. Xu, Multiloop Robust H_inf Control Design Based on Dynamic PLS Approach, Chem. Eng. Res. Des.100, 518-529, 2015.

  • P.-P. Oh, M.-F. Chong, H. L. N. Lau, Y.-M. Choo and J. Chen, Modelling of a Membrane Reactor System for Crude Palm Oil Transesterification. Part II: Transport Phenomena, AIChE Journal,  61(6) 1981-1996, 2015.

  • Y. Liu, T. Chen and J. Chen Auto-Switch Gaussian Process Regression-based Probabilistic Soft Sensors for Industrial Multi-Grade Processes with Transitions, Ind. Eng. Chem. Res., 54(18), 5037-5047, 2015.

  • L. Zhou, J. Chen and Z. Song, Recursive Gaussian Process Regression Model for Adaptive Quality Monitoring in Batch Processes,  2015. (Accepted)

  • Z. Zhang and J. Chen, Correntropy Based Data Reconciliation and Gross Error Detection and Identification for Nonlinear Dynamic Processes, Comput. Chem. Eng.,  75, 120-134, 2015.

  • L. Zhou, J. Chen, Z. Song and Z. Ge, Semi-supervised PLVR Models for Process Monitoring with Unequal Sample Sizes of Process Variables and Quality Variables, J. Process Contr., 26, 1-16, 2015.

  • P. Sun, J. Chen and L. Xie, Self-Active and Recursively Selective Gaussian Process Models for Nonlinear Distributed Parameter Systems, Chem. Eng. Sci.,, 123, 125-136, 2015.

  • X. Cai, P. Sun, J. Chen and L. Xie, ILC Strategy for Progress Improvement of Economic Performance in Industrial Model Predictive Control Systems, J. Process Contr., 24, 107-118, 2014

  • T. Liu, X. Z. Wang and J. Chen, Robust PID Based Indirect-Type Iterative Learning Control for Batch Processes with Time-Varying Uncertainties, J. Process Contr., 24, 95-106, 2014.

  • J. Zhang, M. Jiang and J. Chen, Minimum Entropy-Based Performance Assessment of Feedback Control Loops Subjected to Non-Gaussian Disturbances, J. Process Contr., 24, 1660-1670, 2014.

  • J. Chen and J.-Y. Huang, Texture Analysis of UTDR Images for Enhancement of Monitoring and Diagnosis of Membrane Filtration, Chemometer Intell Lab., 138, 142-152, 2014.

  • Z. Zhang and J. Chen, Simultaneous Data Reconciliation and Gross Error Detection for Dynamic Systems Using Particle Filter and Measurement Test, Comput. Chem. Eng.,  69, 66-74, 2014.

  • Z. Zhang, Y.-Y. Chuang and J. Chen, Methodology of Data Reconciliation and Parameter Estimation for Process Systems with Multi-Operating Conditions, Chemometer Intell Lab., 137, 110-119, 2014.

  • Z. Zhang, Y.-Y. Chuang and J. Chen, Pervasive Knowledge Discovery by Just-in-time Learning to Solve Simultaneous Data Reconciliation and Parameter Estimation of Industrial Processes, Ind. Eng. Chem. Res. 53, 10194-10205, 2014.

  • X. Cai, P. Sun, J. Chen and L. Xie, Rapid Distributed Model Predictive Control Design Using Singular Value Decomposition for Linear Systems, J. Process Contr., 24, 1135-1148, 2014.

  • L. Zhou, J. Chen, Z. Song, Z. Ge and A. Miao, Probabilistic Latent Variable Regression Model for Process-Quality Monitoring, Chem. Eng. Sci., 116, 296-305, 2014.

  • Y. Liu and J. ChenCorrentropy Kernel Learning for Nonlinear System Identification with Outliers, Ind. Eng. Chem. Res., 53(13) 5248-5260, 2014.

  • J. Chen and F. WangCost Reduction of CO2 Capture Processes Using Reinforcement Learning Based Iterative Design: A Pilot-Scale Absorption-Stripping System,Sep. Purif. Technol. 122, 149-158, 2014.

  • L. L. T. Chan, Y. Liu and J. ChenNonlinear System Identification with Selective Recursive Gaussian Process Models, Ind. Eng. Chem. Res. 52(51) 18276-18286, 2013.

  • J. Chen, Y. Peng and J. Munoz, Correntropy Estimator for Data Reconciliation, Chem. Eng. Sci., 104, 1019-1027, 2013.

  • T. Chen, Y. Liu and J. ChenAn Integrated Approach to Active Model Adaptation and On-Line Dynamic Optimisation of Batch Processes, J. Process Contr., 23, 1350-1359, 2013.

  • Y. Liu, Z. Gao and J. Chen, Development of Soft-Sensors for Online Quality Prediction of Sequential-Reactor-Multi-Grade Industrial Processes, Chem. Eng. Sci., 102, 602-612, 2013.

  • J. Chen, Y.-C. Yang and  J.-Y. HuangOn-Line Monitoring and Diagnosis of Membrane Fouling Using Ultrasonic Techniques, Chemometer Intell Lab., 127, 147-157, 2013.

  • Y. Liu and J. Chen, Integrated Soft Sensor using Just-in-time Support Vector Regression and Probabilistic Analysis for Quality Prediction of Multi-grade Processes,  J. Process Contr., 23, 793-804, 2013. 

  • J. Chen, L. L. T. Chan and N. Cheng, Gaussian Process Regression Based Optimal Design of Combustion Systems Using Flame Images, Applied Energy, 111, 153-160, 2013.

  • J. Chen, S.-J. Hsu and T.-Y. Wei, Optimization Design for Removal of Radioactive Kr from Xe Using Pressure Swing Adsorption,  Chem. Eng. Res. Des., 91(4) 649-659, 2013.

  • J. Zhang and J. Chen, Neural PID Control Strategy for Networked Process Control,  Math. Probl. Eng., Article ID 752489,  2013.

  • J. Chen, Y.-H. Chang and Y.-C. Cheng, Performance Design of Image-Oxygen Based Cascade Control Loops for Boiler Combustion Processes, Ind. Eng. Chem. Res., 52(6), 2368–2378, 2013.

  • P.-P. Oh, M.-F. Chong, H. L. N. Lau, J. Chen and Y. M. Choo, Liquid-liquid Equilibrium (LLE) Study for Six-Component Transesterification System, Clean Technologies and Environmental Policy, 15(5), 817–822, 2013.

  • M.-F. Chong, J. Chen, P.-P. Oh and Z.-S. Chen, Modeling Analysis of Membrane Reactor for Biodiesel Production, AIChE J., 59(1) 258-271, 2013.

  • M.-F. Chong, J. Chen, P.-P. Oh and Z.-S. Chen, Modeling Study of Chemical Phase Equilibrium of Canola Oil Transesterification in a CSTR, Chem. Eng. Sci., 87(14) 371-380, 2013.

  • Y.-Y. Lu and J. Chen, Integration Design of Heat Exchanger Networks into Membrane Distillation Systems for Energy Saving, Ind. Eng. Chem. Res., 51(19), 6798–6810, 2012.

  • J. Chen and Y.-H. Lin, Multi-Batch Model Predictive Control for Repetitive Batch Operation with Input-Output Linearization, Ind. Eng. Chem. Res., 51(28) 9598-9608, 2012.

  • P.-P. Oh, H. L. N. Lau, J. Chen, M.-F. Chong and Y. M. Choo, A review on conventional technologies and emerging process intensification (PI) methods for biodiesel production, Renewable and Sustainable Energy Reviews 16, 5131–5145, 2012.

  • J. Chen, Y.-C. Yang and T.-S. Wei, Application of Wavelet Analysis and Decision Tree in UTDR Data for Diagnosis of Membrane Filtration, Chemometer Intell Lab., 116, 102-111, 2012 .

  • J. Chen, J. Munoz and N. Cheng, Deterministic and Stochastic Model Based Run-to-Run Control for Batch Processes with Measurement Delays of Uncertain Duration, J. Process Contr., 22, 508-517, 2012.

  • J. Chen, Y.-H. Chang, Y.-C. Cheng and C.-K. Hsu, Design of Image-Based Control Loops for Industrial Combustion Processes, Applied Energy, 94, 13-21, 2012.

  • J. Munoz and J. Chen, Removal of the Effects of Outliers in Batch Process Data through Maximum Correntropy Estimator, Chemometer Intell Lab.. 111(1) 53-58, 2012.

  • L.-H. Cheng, S.-Y. Yen, Z.-S. Chen and J. Chen, Modeling and Simulation of Biodiesel Production Using a Membrane Reactor Integrated with a Pre-reactor, Chem. Eng. Sci., 69(1) 81-92, 2012.

  • Y.-Y. Lu, J. Chen, T.-C. Liu and M.-H, Chien, Using Cooling Load Forecast as the Optimal Operation Scheme for a Large Multi-Chiller System, Int. J. of Refrigeration, 34, 2050-2062, 2011.

  • L.-H. Cheng,Y.-H. Lin and J. Chen, Enhanced Air Gap Membrane Desalination by Novel Finned Tubular Membrane Modules, J. Membr. Sci. 378(1-2) 398-406, 2011.

  • J. Chen, K.-Y. Liu and J. Munoz, Context-KSVM-PLS Based Run-to-Run Control for Nonlinear MIMO Processes, Int. J. Innov. Comput. I. 7(7B) 4139-4148, 2011.

  • Y.-Y. Lu and J. Chen, Optimal Design of Multi-Stage Membrane Distillation Systems for Water Purification, Ind. Eng. Chem. Res. 50(12) 7345-7354, 2011.

  • J. Chen and Y.-C. Jiang, Hidden Semi-Markov Probability Models for Monitoring Two-Dimensional Batch Operation, Ind. Eng. Chem. Res. 50(6) 3345-3355, 2011.

  • L.-H. Cheng, Y.-C. Yang, J. Chen, Y.-H. Lin and S.-H. Wang, A New View of Membrane Fouling with 3D Ultrasonic Imaging Techniques: Taking the Canola Oil with Phospholipids for Example,  J. Membr. Sci. 372(1-2) 134-144, 2011.

  • J. Chen, Hsu, T.-Y. Hsu, C.-C. Chen and Y.-C. Cheng, On-Line Predictive Monitoring Using Dynamic Imaging of Furnaces with the Combinational Method of MPCA and HMM, Ind. Eng. Chem. Res.50(5) 2946-2958, 2011.

  • J. Chen and Y.-C. Jiang, Development of Hidden Semi-Markov Models for Diagnosis of Multiphase Batch Operation, Chem. Eng. Sci., 66, 1087-1099, 2011.

  • J. Chen and W.-Y. Wang, Performance Monitoring of MPCA Based Control for Multivariable Batch Control Processes,  J. Taiwan Inst. Chem. Eng., 41, 465-474, 2010.

  • J. Chen, M.-H. Chen and L. L. T. Chan, Iterative Learning Parameter Estimation and Design of SMB Processes, Chemical Engineering Journal, 161, 223-233, 2010.

  • L.-H. Cheng, S.-Y. Yen, L.-S. Su and J. Chen, Study on Membrane Reactors for Biodiesel Production by Phase Behaviors of Canola Oil Methanolysis in Batch Reactors,  Bioresource Technology, 101, 6663-6668, 2010.

  • J. Chen, K.-T. Hsieh and L. L. T. Chan, Wave Propagation Velocities in Integrated PLS Based Control of a Simulated Moving Bed Process, Chem. Eng. Sci., 65, 2990-3000, 2010

  • J. Chen, K.-Y. Liu and J. Munoz, Context-KSVM Based Run-to-Run Control for Nonlinear Processes, Korean J. Chem. Eng., 27(5). 1366-1371, 2010.

  • J. Chen, T.-Y. Hsu, C.-C. Chen and Y.-C. Cheng, Monitoring Combustion Systems Using HMM Probabilistic Reasoning in Dynamic Flame Images, Applied Energy, 87, 2169-2179, 2010.

  • J. Chen, C.-M. Song and T.-Y. Hsu, On-Line Monitoring of Batch Processes Using IOHMM Based MPLS, Ind. Eng. Chem. Res., 49(6) 2800-2811, 2010.

  •  J. Chen and W.-Y. Wang, PCA-ARMA Based Control Charts for Performance Monitoring of Multivariable Feedback Control, Ind. Eng. Chem. Res., 49(5) 2228-2241, 2010.

  • L.-H. Cheng, Y.-F. Cheng, S.-Y. Yen and J. Chen, Application of UNIQUAC and SVM to Ultrafiltration for Modeling Ternary Mixtures of Oil, FAME and Methanol, Chem. Eng. Sci., 64(24) 5093-5103, 2009.

  • J. Chen and K.-T. Chou, Iterative Learning Controller Synthesis Using FIR Models for Batch Processes, Korean J. Chem. Eng., 26(6) 1512-1518, 2009..

  • J. Zhang, C.-C. Chu, J. Munoz and J. Chen, Minimum Entropy Based Run-to-Run Control for Semiconductor Processes with Uncertain Metrology Delay, J. Process Contr., 19, 1688-1697, 2009

  • J. Chen and R.-K. Tsai, Development of MBPLS Based Control for Serial Operation Processes, Korean J. Chem. Eng., 26(4) 935-945, 2009.

  • L.-H. Cheng, P.-C. Wu and J. Chen, Numerical Simulation and Optimal Design of AGMD-Based Hollow Fiber Modules for Desalination , Ind. Eng. Chem. Res., 48(10) 4948-4959, 2009.

  • J. Chen and C.-K. Kong, Performance Assessment for Iterative Learning Control of Batch Units, J. Process Contr., 19(6), 1043-1053, 2009.

  • L.-H. Cheng, Y.-F. Cheng, S.-Y. Yen and J. Chen, Ultrafiltration of Triglyceride from Biodiesel Using the Phase Diagram of Oil-FAME-MeOH, J. Membr. Sci., 330, 156-165, 2009.

  • J. Chen, K.-T. Hsieh and L. L. T. Chan, PLS Data-Driven Based Approach to Design of a Simulated Moving Bed Process, Sep. Purif. Technol., 65, 173-183, 2009

  • J. Chen,  C.-J. Hsu and C.-C. Chen,  A Self-Growing Hidden Markov Tree for Wafer Map Inspection, J. Process Contr., 19, 261-271, 2009.

  • J. Chen and K.-C. Lin, Integrated Batch-to-Batch Control and within-Batch On-Line Control for Batch Processes Using Two-Step MPLS-Based Model Structures, Ind. Eng. Chem. Res., 47 (22) 8693-8703, 2008.

  • L.-H. Cheng, P.-C. Wu and J. Chen, Modeling and Optimization of Hollow Fiber DCMD Module for Desalination, J. Membr. Sci., 318, 154-166, 2008.

  • L.-H. Cheng, P.-C. Wu, C.-K. Kong and J. Chen, Spatial Variations of DCMD Performance for Desalination through Countercurrent Hollow Fiber Modules, Desalination, 234, 323-334, 2008.

  • J. Chen and K.-C. Lin, Batch-to-Batch Iterative Learning Control and within-Batch On-Line Control for End-Point Qualities Using MPLS Based dEWMA, Chem. Eng. Sci., 63, 977-990, 2008.

  • L.-H. Cheng, Y.-F. Cheng and J. Chen, Predicting Effect of Interparticle Interactions on Permeate Flux Decline in CMF of Colloidal Suspensions: An Overlapped Type of Local Neural Network, J. Membr. Sci., 308 (1-2) 54-65, 2008.

  • J. Chen, C.-J. Hsu, Y.-C. Jiang and M.-W. Lee, A Self-Growing HMT based MPCA for Enhanced Monitoring of Batch Processes, Ind. Eng. Chem. Res., 46 (18) 6010-6024, 2007.

  • J. Chen and F. Wang, PLS Based dEWMA Run-to-Run Controller for MIMO Non-Squared Semiconductor Processes, J. Process Contr., 17 (4) 309-319, 2007.

  • J. Chen and Y. Yea, Controlled Output Variance Based Diagnosis Tree for Feedforward/Feedback Control Systems, Chem. Eng. Sci., 62 (4) 943-956, 2007.

  • J. Chen, K.-C. Lin and C.-K. Kong, Application of the Batch-to-Batch and Within-Batch Iterative Optimal Design Strategy for Pervaporation Processes, Sep. Purif. Technol., 55, 265-273, 2007.

  • J. Chen and C.-K. Kong, Controlled Output Variance Based Diagnosis Tree for Feedforward/Cascade Control Systems, Korean J. Chem. Eng., 24(3) 379-390, 2007.

  • J. Chen,  H. Chang and S.-R. Chen, Simulation Study of a Hybrid Absorber– Heat Exchanger Using Hollow Fiber Membrane Module for the Ammonia-Water Absorption Cycle, Int. J. of Refrigeration, 29 1043-1052, 2006.

  • J. Chen, Y. Yea and C.-K. Kong, Diagnosis of Cascade Control Loop Status Using Performance Analysis Based Approach, Ind. Eng. Chem. Res., 45 (22) 7540-7551, 2006.

  • J. Chen and H.-H. Chen, On-Line Batch Process Monitoring Using MHMT Based MPCA, Chem. Eng. Sci., 61 (10) 3223-3239, 2006

  • H. Chang, J. Chen and Y.-P. Ho, Batch Process Monitoring by Wavelet Transform Based Fractal Encoding, Ind. Eng. Chem. Res., 45(11) 3864-3879, 2006 

  • J. Chen, K.-P. Wang, J.-Y. Houng and C.-H. Liao, Sequential Design of pH Profiles for Asymmetric Bioreduction of Ethyl 4-Chloro-3-Oxobutyrate Using a New Experimental Design Method, Enzyme Microb. Technol., 38 (5) 689-696, 2006 

  • Y. Yea and J. Chen, Diagnosis of Closed Control Loop Status Using Performance Analysis Based Approach, Ind. Eng. Chem. Res., 44 (15) 5660-5671, 2005

  • J. Chen and W.-J. Chang, Applying Wavelet-Based Hidden Markov Tree to Enhancing Performance of Process Monitoring, Chem. Eng. Sci., 60 (18) 5129-5143, 2005

  • J. Chen, S.-C. Huang and Y. Yea, Achievable Performance Assessment and Design for Parallel Cascade Control Systems, J. Chem. Eng. Jpn., 38 (3) 181-201, 2005.

  • J. Chen, Y.-C. Chang and Y. Yea, Multiloop PID Controller Design Using PLS Decoupling Structure, Korean J. Chem. Eng., 22 (2) 173-183, 2005

  • J. Chen, K.-P. Wang  and M.-T. Liang, Predictions of Heat Transfer Coefficients of Supercritical Carbon Dioxide Using the Overlapped Type of Local Neural Network, Int. J. Heat Mass Transf., 48 (12) 2483-2492, 2005.

  • J. Chen and Y.-C. Cheng, Applying PLS-Based Decomposition Structure to Multi-Loop Adaptive PID Controllers in Nonlinear Processes, Ind. Eng. Chem. Res., 43 (18) 5888-5898, 2004. 

  • J. Chen and K.-P. Wang, Sequential Experimental Design Strategy for Optimal Batch Profiles Using Hybrid Function Approximations, Ind. Eng. Chem. Res., 43 (17) 5260-5274, 2004. 

  • J. Chen and T.-C. Huang Applying Neural Networks to On-line Updated PID Controllers for Nonlinear Process Control, J. Process Control, 14 (2) 211-230, 2004.

  • J. Chen and J.-H. Yen, Three-Way Data Analysis with Time Lagged Window for On-Line Batch Process Monitoring, Korean J. Chem. Eng., 20 (6) 1000-1011,2003 

  • J. Chen and Y. Yea, Design Pole Placement Controller Using Linearized Neural Networks for MISO Systems, J. Chem. Eng. Jpn., 1005-1011, 2003.

  • J. Chen and R.-G. Sheui, Optimal Batch Trajectory Design Based on an Intelligent Data-Driven Method,  Ind. Eng. Chem. Res., 42 (7) 1363-1378, 2003. 

  • J. Chen and Y. Yea, Modified QDMC Based on Instantaneous Linearization of Neural Network Models in Nonlinear Chemical Processes, J. Chem. Eng. Jpn., 36 (2) 198-209, 2003.

  • J. Chen, K.-P. Wang, J.-Y. Houng and S.-L. Lee, Design of pH Profile for Asymmetric Bioreduction of Ethyl 4-Chloro Acetoacetate on the Basis  of a Data-Driven Method, Biotechnol. Prog., 8 (6) 1414-1422, 2002.

  • J. Chen and Y. Yea, Neural Network-Based Predictive Control for Multivariable Processes, Chem. Eng. Commun., 189 (7) 865-894, 2002.

  • J. Chen and and R.-G. Sheui, Using Taguchi’s Method and Orthogonal Function Approximation to Design Optimal Manipulated Trajectory in Batch Processes,  Ind. Eng. Chem. Res., 41(9) 2226-2237, 2002.

  • J. Chen, Y. Yea and C.-W. Wang, Neural Network Model Predictive Control for Nonlinear MIMO Processes with Unmeasured Disturbances, J. Chem. Eng. Jpn., 35(2) 150-159,  2002. 

  • J. Chen and K.-C. Liu, On-Line Batch Process Monitoring Using Dynamic PCA and Dynamic PLS Models, Chem. Eng. Sci., 57 (1) 63-75, 2002. 

  • J. Chen and C.-M. Liao, Dynamic Process Fault Monitoring Based on Neural Network and PCA, J. Process Control, 12 (2) 277-289, 2002.  

  • J. Chen, C.-M. Liao, F. R.-J. Lin and M.-J. Lu, PCA Based Control Charts with Memory Effect for Process Monitoring, Ind. Eng. Chem. Res., 40 (6), 1516-1527, 2001.

  • J. Chen and J. Liu, Derivation of Function Space Analysis Based PCA Control Charts for Batch Process Monitoring, Chem. Eng. Sci., 56 (10), 3289-3304, 2001.

  • J. Chen and J. Liu, Using Mixture PCA Networks to Extract Fuzzy Rules from Data, Ind. Eng. Chem. Res., 39 (7), 2355-2367, 2000.

  • J. Chen and J. Liu, Post Analysis on Different Operating Time Processes Using Orthonormal Function Approximation and Multiway Principal Component Analysis, J. Process Control, 10 (5), 411-418, 2000.

  • J. Chen, S.-S. Jang, D. S. H. Wong, C.-C. M. Ma and J.-M. Lin, Optimal Design of Filament Using Neural Network Experimental Scheme, J. of Composite Materials, 33 (24), 2281-2300, 1999.

  • J. Chen and J. Liu, Mixture PCA Models for Process Monitoring, Ind. Eng. Chem. Res., 38 (4), 1478-1488, 1999.

  • J. Chen, P. P.-T. Chu, D. S. H. Wong, and ,S.-S. Jang Optimal Design Using Neural Network and Information Analysis in Plasma Etching, J. Vac. Sci. Technol. B, 17, 145-153, 1999.

  • J. Chen, D. S. H. Wong, S.-S. Jang, and S.-L. Yang, Product and Process Development Using Artificial Neural Network Model and Information Theory, AIChE J., 44, 876-887, 1998.

  • J. Chen, Systematic Derivation of Model Predictive Control Based on Artificial Neural Network, Chem. Eng. Commun., 164, 35-59, 1998.

  • J. Chen and D. D. Bruns, Recursive Nonlinear System Identification Using an Adaptive WaveARX Network, Ind. Eng. Chem. Res., 35, 2782-2789, 1996.

  • J. Chen and D. D. Bruns, WaveARX Neural Network Development for System Identification Using A Systematic Design Synthesis, Ind. Eng. Chem. Res., 34, 4420-4435, 1995.

  • Y.-S. Lee, S.-K. Ooi and J. Chen, Developing Long-term Quality Multistep-ahead Prediction Models for Early Warning, 10th The International Symposium on Design, Operation & Control of Chemical Processes (PSE Asia 2022), Dec. 10-14, 2022, Indian Institute of Technology Madras Campus, Indian. (Accepted)

  • L.-X. You, and J. Chen, Meta-learning based Functional ODE Model for Monitoring Continuous Multimode Process with Irregular Sampling Data, 10th The International Symposium on Design, Operation & Control of Chemical Processes (PSE Asia 2022), Dec. 10-14, 2022, Indian Institute of Technology Madras Campus, Indian. (Accepted)

  • P.-H. Chen, J. Chen and J. Liu, Automatic Segmentation of Dynamic and Static Models Based on High Order Slow Feature Analysis for Multiphase Batch Monitoring, 10th The International Symposium on Design, Operation & Control of Chemical Processes (PSE Asia 2022), Dec. 10-14, 2022, Indian Institute of Technology Madras Campus, Indian. (Accepted)

  • K.-H. Chiu, and J. Chen, Dynamic Data Reconciliation Using Conditional Dynamic Variational Autoencoders with Particle Filters to Enhance Process Monitoring Performance, 10th The International Symposium on Design, Operation & Control of Chemical Processes (PSE Asia 2022), Dec. 10-14, 2022, Indian Institute of Technology Madras Campus, Indian. (Accepted)

  • Y.-S. Lee, and J. Chen, Quality Prediction for Nonlinear Dynamic Processes Using Semi-Supervised Soft-sensors: An Application to Ammonia Decarburization Processes, 7th International Symposium on Advanced Control of Industrial Processes (ADCONIP 2022), 7-9 Aug, 2022, UBC Vancouver, Canada. (Virtual)

  • Y.-S. Lee  and J. Chen, Enhancing Monitoring Performance of Pharmaceutical Processes Using Dual-Attention Latent Dynamic Conditional State-Space Model, 13th Asian Control Conference (ASCC 2022), May 3-7, 2022, Jeju Island, Korea.  (Virtual)

  • J. Liu, G. Mu and J. Chen, Tensor Slow Feature Analysis for Monitoring Batch Process, 13th Asian Control Conference (ASCC 2022), May 3-7, 2022, Jeju Island,, Korea.  (Virtual)

  • Y.-S. Lee, O. S. Kit, D. Tanny and J. Chen, Maintaining Soft-Sensor Models Using Latent Dynamic Variational Autoencoders, 11th International Symposium on Advanced Control of Chemical Processes (ADCHEM), June 13-16, 2021, Venice, Italy. (Virtual)

  • D. Tanny and J. Chen, Developing Dynamic Soft Sensor Based Variational Autoencoders, 9th The International Symposium on Design, Operation & Control of Chemical Processes (PSE Asia 2020), Nov. 4-6, 2020, Taipei. (Virtual)

  • Y.-S. Lee and J. Chen, Boosting Monitoring Performance for Nonlinear Processes with Limited Samples Using Gaussian Mixture Latent Distribution in Variational Autoencoders, 9th The International Symposium on Design, Operation & Control of Chemical Processes (PSE Asia 2020), Nov. 4-6, 2020, Taipei. (Virtual)

  • Y.-C. Zhang, L. L. T. Chan and J. Chen, Application of Convolutional Neural Network Based Variational Auto-encoder Model to the Image Monitoring of Combustion Processes, 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), Sept. 23-26, 2020, Chiang Mai, Thailand. (Virtual)

  • D. Tanny, J. Chen and K. Wang, Developing Variational Autoencoders with Differential Entropy Soft Sensor Models for Nonlinear Processes, 21st IFAC World Congress, July 12-17, 2020, Berlin, Germany. (Virtual)

  • K. Wang, J. Chen and Y. Wang, Developing a deep learning estimator to learn nonlinear dynamic systems, 21st IFAC World Congress, July 12-17, 2020, Berlin, Germany. (Virtual)

  • L. Zhu, Z. Li and J. Chen, An Industrial Process Monitoring Scheme with Moving Window Slow Feature Analysis, 21st IFAC World Congress, July 12-17, 2020, Berlin, Germany. (Virtual)

  • Q. Chen, J. Chen, X. Lang, L. Xie, C. Jiang and H. Su, Detecting and Characterizing Nonlinearity-induced Oscillations in Process Control Loops Based on Adaptive Chirp Mode Decomposition, 2020 American Control Conference, July 1-3, 2020, Denver, CO, USA. (Virtual)

  • Z. Li, J. Chen and C.-I. Chen, Prognostics of Tool Failing Behavior Based on Auto-associative Gaussian Process Regression for Semiconductor Manufacturing, 2020 IEEE International Conference on Industrial Technology (ICIT) , Feb. 26-28, 2020, Buenos Aires, Argentina. (Virtual)

  • L. L. T. Chan and J. Chen, Reducing Cost of Process Modeling through Multi-source Data Transfer Learning, 12th Asian Control Conference (ASCC), June. 9-12, 2019, Fukuoka, Japan. 

  • K. Wang, J. Chen and Z. Song, Fault Detection Based on Variational Autoencoders for Complex Nonlinear Processes, 12th Asian Control Conference (ASCC), June. 9-12, 2019, Fukuoka, Japan.

  • P. Lu, J. Chen,  L. Xie and H. Su, A Robust Integrated Economic Optimization for Batch Processes Using Disturbances Based Dual-Feedback Control, 8th The International Symposium on Design, Operation & Control of Chemical Processes (PSE Asia 2019), Jan. 13-16, 2019, Bangkok, Thailand.

  • K. Wang, J. Chen,  L. Xie and H. Su, A New Optimization Frame Work of Integration Design and Control Using Gaussian Model under Uncertainty, 8th The International Symposium on Design, Operation & Control of Chemical Processes (PSE Asia 2019), Jan. 13-16, 2019, Bangkok, Thailand.

  • L. L. T. Chan, Y.-S. Lee and J. Chen, Economic Model Predictive Control of CO2 Capture Process Retrofitted with Membrane Units, 6th International Symposium on Process Intensification, Nov. 7-8, 2018, Taipei, Taiwan.

  •  Y.-S. Lee, O.-S. Kit, D. Tanny, L. L. T. Chan and J. Chen, Reducing Energy Cost of Absorber-Stripper CO2 Capture Process through Economic Neural Network Model Predictive Control, 6th International Symposium on Process Intensification, Nov. 7-8, 2018, Taipei, Taiwan.

  • L. L. T. Chan and J. Chen, Economic Model Predictive Control of an Absorber-Stripper CO2 Capture Process for Improving Energy Cost, 10th International Symposium on Advanced Control of Chemical Processes (ADCHEM), July 25-27, 2018, Shenyang, China.

  • Y. Lyu, J. Chen and Z. Song, Image-Based Process Monitoring Using Deep Belief Networks, 10th International Symposium on Advanced Control of Chemical Processes (ADCHEM), July 25-27, 2018, Shenyang, China.

  • P. Lu, J. Chen and L. Xie, ILC Based Economic Batch-to-Batch Optimization for Batch Processes, 10th International Symposium on Advanced Control of Chemical Processes (ADCHEM), July 25-27, 2018, Shenyang, China.

  • J. Liu, T. Liu and J. Chen, Quality Prediction for Multi-Grade Processes by Common and Special Feature Extraction, 10th International Symposium on Advanced Control of Chemical Processes (ADCHEM), July 25-27, 2018, Shenyang, China.

  • P. Lu, J. Chen and L. Xie, Development of Decay Based PLS Model and Its Economic Run-to-Run Control for Semiconductor Processes, 2018 American Control Conference, June 27-29, 2018, Milwaukee, USA.

  • C.-H. Wei, J. Chen and Z.-H. Song, Soft Sensors of Nonlinear Industrial Processes Based on Self-Learning Kernel Regression Model, proceedings of 2017 Asian Control Conference, (ASCC 2017), December 17-20, 2017, Gold Coast, Australia.

  • L. Zhou, J. Chen, Z. Ge and Z.-H. Song, Multiple Fault Detection Using Multi-rate Probability Principle Component Analysis Models, 20th IFAC World Congress, 9-14 July 2017, Toulouse, France.

  • X. Wu, L. L. T. Chan, J. Chen and X. Lei, Application of Gaussian Processes with Variable Shrinkage Method and Just-In-Time Modeling in the Semiconductor Industry, 6th International Symposium on Advanced Control of Industrial Processes (ADCONIP 2017), 28-31 May, 2017, Taipei.

  • Z. Yan, J. Chen and Z. Zhang, Valve Stiction Detection Using the Bootstrap Hammerstein System Identification, 6th International Symposium on Advanced Control of Industrial Processes (ADCONIP 2017), 28-31 May, 2017, Taipei.

  • S. W. Ku, J. Chen and L. L. T. Chan, Identification of LTV Systems with Cascade Control Loops Using Basis Function Approach, 6th International Symposium on Advanced Control of Industrial Processes (ADCONIP 2017), 28-31 May, 2017, Taipei.

  • Q.-Y. Wu, L. L. T. Chan and J. Chen, Active Learning Dynamic Soft Sensor with Forward-Update Scheme, 6th International Symposium on Advanced Control of Industrial Processes (ADCONIP 2017), 28-31 May, 2017, Taipei.

  • X. Lang, D. Zhong, L. Xie, J. Chen and H. Su, Application of the Improved Multivariate Empirical Mode Decomposition to Plant-Wide Oscillations Characterization, 6th International Symposium on Advanced Control of Industrial Processes (ADCONIP 2017), 28-31 May, 2017, Taipei.

  • J. Chen, L. L. T. Chan and Q.-Y. Wu, Utilizing Big Data for Development of Soft Sensor, AIChE's 2017 Spring Meeting and 13th Global Congress on Process Safety, San Antonio, US, Mar. 26-30 2017,

  • Q.-Y. Wu, Y. Liu and J. Chen, LTV Gaussian Process Assisted Data Selection for Sequential Quality Enhancement of Latent Variable Soft Sensor Models, 7th The International Symposium on Design, Operation & Control of Chemical Processes (PSE Asia 2016), Tokyo, Japan, July 24-27, 2016.

  • C.-H. Wei, J. Chen and Z.-H. Song, Process Fault Classification Based on Supervised Maximum Variance Unfolding, 7th The International Symposium on Design, Operation & Control of Chemical Processes (PSE Asia 2016), Tokyo, Japan, July 24-27, 2016.

  • S.-W. Gu and J. Chen, LTV Subspace System Identification for Nonlinear Chemical Processes – An Orthonormal Basis Function Approach, 7th The International Symposium on Design, Operation & Control of Chemical Processes (PSE Asia 2016), Tokyo, Japan, July 24-27, 2016.

  • L. L. T. Chan,  C.-P. Chou and J. Chen,  Hybrid Model Based Control for Membrane Filtration Process, 11th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems (DYCOPS-CAB 2016),   Trondheim, Norway, June 6-8, 2016.

  • L. L. T. Chan and J. Chen, Gaussian Process Model Based Performance Assessment of Control Loop, 17th IFAC Symposium on System Identification (SYSID 2015),  Oct 19-21, 2015 , Beijing.

  • L. L. T. Chan, Z. Ge and J. Chen, A Distributed Modeling Framework for Monitoring Big Data in Plant-Wide Processes, AIChE's 2015 Spring Meeting and 11th Global Congress on Process Safety,  26-30 Apr. 2015, Austin, US.

  • J. Chen, J. Zhang and L. Zhang, Entropy Information Based Assessment of Cascade Control Loops, International MultiConference of Engineers and Computer Scientists 2013 (IMECS 2015), 18-20 Mar. 2015, Hong Kong.

  • L. Zhou, Z.-H. Song, J. Chen, Z. Ge, L Zhao, Process-Quality Monitoring Using Semi-supervised Probability Latent Variable Regression Models 19th IFAC World Congress, 24-29 August, 2014, Cape Town, South Africa.

  • L. T. L. Chan, T. Chen, J. Chen, Applying Gaussian Process Models to On-line Enhancement of PID Control Design for Nonlinear Processes, 5th  International Symposium on Advanced Control of Industrial Processes (ADCONIP 2014), 28-30 May, 2014, Hiroshima, Japan.

  • Y. Liu and J. Chen, Correntropy-Based Kernel Learning for Nonlinear System Identification with Unknown Noise: An Industrial Case Study, 10th IFAC Symposium on Dynamics and COntrol of Process Systems, DYCOPS2013, December 18-20, 2013, Mumbai, India.

  • J. Chen, L.-S. Su, J. Munoz and Y.-C. Cheng,  Image Distribution Model Based Iterative Learning Control for Combustion Processes, PSE Asia 2013, 25-27 June. 2013,  Kuala Lumpur, Malaysia.

  • J. Chen and Y.-C. Yang, Real-time Ultrasonic Monitoring of Membrane Fouling, International MultiConference of Engineers and Computer Scientists 2013 (IMECS 2013), 13-15 Mar. 2013, Hong Kong.

  • J. Munoz and J. Chen, Performance Assessment of Feedback Control Loops for Processes with Distribution Outputs, 11th International Symposium on Process Systems Engineering, PSE2012, 15-19 Jul.. 2012, Singapore.

  • J. Chen and Y.-C. Yang, UTDR Based Diagnosis for Membrane Filtration, International MultiConference of Engineers and Computer Scientists 2012 (IMECS 2012), 14-16 Mar. 2012, Hong Kong.

  • J. Chen,  N. Cheng and Y.-C. Cheng, Hybrid Model Based Iterative Learning Control for Semiconductor Processes with Uncertain Metrology Delay, 4th IEEE Conference on Industrial Electronics and Applications (ICIEA 2011), 21-23 June 2011, Beijing, China.

  • J. Chen, N. Cheng and J. Zhang, Neural Based PID Control for Communication Network Processes, 4th Conference on Advanced Control of Industrial Processes 2010 (ADCONIP 2011), May 23-26, 2011, Hangzhou, China.

  • J. Chen and Y.-C. Yang, UTDR Based Diagnosis for Membrane Filtration, International MultiConference of Engineers and Computer Scientists 2011 (IMECS 2011), 16-18 Mar. 2011, Hong Kong.

  • J. Chen Y.-H. Chang and Y.-C. Cheng, Performance Assessment of the Combustion Control Loop, 2010 International Conference on Measurement and Control Engineering (ICMCE 2010), 16-18, Nov. 2010, Chengdu, China.

  • J. Munoz, N. Cheng and J. Chen, Using Adaptive Wavelet Method and Correntropy in Estimating Density Distribution Functions of Data with Outliers, The 13th Asia Pacific Confederation of Chemical Engineering Congress (APCChE 2010), 5-8 Oct., 2010, Taipei.

  • C.-C. Chu, J. Munoz and J. Chen, Run-to-Run Control Design Based on Deterministic and Stochastic Models, PSE Asia 2010, 25-28 July, 2010, Singapore.

  • J. Chen, T.-Y. Hsu, Image Based Monitoring for Combustion Systems, International MultiConference of Engineers and Computer Scientists 2010 (IMECS 2010), 17-19 Mar. 2010, Hong Kong.

  • J. C. Munoz and J. Chen, Adaptive Wavelet Density Distribution for Modeling Polymerization Processes, 16th ASEAN Regional Symposium of Chemical Engineering, 1-2 Dec. 2009, Manila, Philippines.

  • J. Chen and Y.-C. Jiang, Monitoring Multiphase Batch Operations Using Hidden Semi-Markov Statistical Model, IASTED International Conference on Modelling, Simulation and Identification, 12-14 Oct. 2009, Beijing, China.

  • J. Chen, C.-C. Chu, J. Munoz and J. Zhang, Iterative Learning Control for Processes with Uncertain Time Delay Using Minimum Entropy, 7th Asian Control Conference, ASCC09, August, 2009, Hong Kong.

  • L.-H. Cheng, Y.-C. Yang, J. Chen, T.-S. Chang Y.-H. Lin and S.-H. Wang, Ultrasonic Image Analysis for Membrane Fouling in Ultrafiltration of Phospholipids from Crude Oil, The Fifth Conference of Aseanian Membrane Society, July, 2009, Kobe, Japan.

  • J. Chen and W.-Y. Wang, Performance Assessment of Multivariable Control Systems using PCA Control Charts, 4th IEEE Conference on Industrial Electronics and Applications (ICIEA 2009), 25-27 May 2009, X'ian, China.

  •  J. Chen and R.-K. Tsai, Development of MBPLS Based Control for Serial Operation Processes, 2009 World Congress on Computer Science and Information Engineering (CSIE 2009), 31 Mar.-2 Apr. 2009, Los Angeles/Anaheim, USA.

  • J. Chen and C.-M. Song, Input-Output Hidden Markov Model-Based On-Line Monitoring for Batch Operation, International MultiConference of Engineers and Computer Scientists 2009 (IMECS 2009), 31-20 Mar. 2009, Hong Kong.

  • T.-Y. Hsu, L. C. L. Teck, J. Chen, M.-T. Liang and R.-C. Liang, Fault monitoring of SMB processes using visualized on-line concentration patterns, 2008 Taiwan/Korea/Japan ChE Conference, 20-22 Nov. 2008, Taipei, Taiwan.

  •  C.-C. Chu, J. Munoz and J. Chen, Minimum Entropy Approach of Run-to-Run Control for Semiconductor Processes with Uncertain Time Delay, 2008 Taiwan/Korea/Japan ChE Conference, 20-22 Nov. 2008, Taipei, Taiwan.

  • M.-H. Chen, L. L. T. Chan, J. Chen and M.-T. Liang, Performance Monitoring of SMB Operation Using UV On-Line Systems, International Symposium on Preparative & Industrial Chromatography and Allied Techniques,  SPICA 2008, Sep. 28--Oct. 1, 2008, Zurich, Switzerland.

  •  T.-Y. Hsu, L. L. T. Chan, J. Chen and M.-T. Liang, Modeling Study of On-Line Estimation of SMB Parameters in Mixture of Quercetin and Rutin, International Symposium on Preparative & Industrial Chromatography and Allied Techniques,  SPICA 2008, Sep. 28--Oct. 1, 2008, Zurich, Switzerland.

  •  L.-H. Cheng, Y.-F. Cheng and J. Chen, Ultrafiltration Removal of Triglyceride from Biodiesel Using the Phase Diagram of Oil-Methyl Oleate-Methanol, ICOM 2008, July 12-18, 2008, Honolulu, Hawaii, USA.

  • J. Chen and C.-K. Kong, Performance Assessment Measures of Batch Processes for Iterative Learning Control, 17th IFAC World Congress, July 6-11, 2008, Seoul, Korea.

  • Y.-F. Cheng, S.-Y. Yen, L.-H. Cheng and J. Chen, Ternary Phase Diagram of Oil-FAME-MeOH and its application to the oil separation from Biodiesel, International Membrane Conference in Taiwan 2008 (2008 IMCT), June 27, 2008, Chung-Li, Taiwan.

  •  J. Chen and K.-C. Lin, Two-Step MPLS-Based Iterative Learning Control for Batch Processes, International MultiConference of Engineers and Computer Scientists 2008 (IMECS 2008), March 2008, Hong Kong.

  • L.-H. Cheng, P.-C. Wu, C.-K. Kong and J. Chen, Modeling of Countercurrent Hollow Fiber Module for DCMD of Desalination, The Fourth Conference of Aseanian Membrane Society, August 2007, Taipei, Taiwan.

  • K.-T. Hsieh, L. L. T. Chan, and J. Chen, PLS-based Iterative Control of a Simulated Moving Bed, PSE Asia 2007, August 2007, Xi'an, China.

  •  J. Chen and C.-J. Hsu, A Self-Growing Hidden Markov Tree for Batch Process Monitoring, 2nd IEEE Conference on Industrial Electronics and Applications (ICIEA 2007), May 2007, Harbin, China.

  •  J. Chen and K.-C. Lin,  Batch-to-Batch and within-Batch Control for Batch Processes Using MPLS-dEWMA Models, International MultiConference of Engineers and Computer Scientists 2007 ( IMECS 2007), March 2007, Hong Kong.

  •  J. Chen and F. Wang, PLS Based Iterative Learning Control Scheme for Batch Systems, AIChE Annual Meeting, November 2006, San Francisco, U.S.A.

  • J. Chen,  Y. Yea and C.-K. Kong, Fault Detection of Cascade Control System Based on Output Performance, 1st IEEE Conference on Industrial Electronics and Applications (ICIEA 2006), May 2006, Singapore. 

  • J. Chen, H.-H. Chen and W.-J. Chang, Wavelet-Based Hidden Markov Tree for Batch Process Monitoring, PSE Asia, August, 2005, Seoul, Korea.

  • J.  Chen  and F. Wang,  PLS Based dEWMA Controller for MIMO Non-Squared Semiconductor,  International Conference on Engineering Applications and Computational Algorithms (DCDIS), July 2005, Ontario, Canada.

  • J.  Chen  and Y. Yea, Assessment and Diagnosis of Feedforward/Feedback Control System, American Control Conference (ACC 2005), June 2005,  Portland, Oregon.

  • F. Wang and J. Chen, PLS Based Run-to-Run Control Design for MIMO Non-Squared Semiconductor Processes, 2004 Symposium on Process Systems Engineering, December 2004, Taichung, R.O.C.

  • S.-C. Huang, Y. Yea, K.-C. Kai and J. Chen, Performance Assessment Measures for Parallel Cascade Control, 2004 Symposium on Process Systems Engineering, December 2004, Taichung, R.O.C.

  •  J. Chen, Y. Yea, F. Wang and Y.-P. Ho, On-Line Batch Process Monitoring Using Three-Way Data Analysis,” Proceedings of the 2004 CIChE Annual Meeting and Conferences, November 2004, Tainan, R.O.C.

  • J. Chen and Y.-C. Cheng, Using Neural Networks and PLS to Design Multi-loop PID Controllers in Nonlinear MIMO Processes, 2004 International Conference on Dynamics, Instrumentation and Control (CDIC'04), Nanjing, China. 

  • S.-C. Huang, Y. Yea and J. Chen, Achievable Performance Design of Single-Loop PID Control Systems, 2003 Symposium on Process Systems Engineering, 213-219, Taipei.

  • P.-S. Huang and J. Chen,  Identification of Hammerstein Models Using CMAC Network, 2003 Symposium on Process Systems Engineering, 289-297, Taipei.

  • J. Chen, Y. Yea, W.-J. Chang and S.-C. Huang, Optimal Batch Trajectory Design Based on An Intelligent Data-Driven Method, Proceedings of the 2003 CIChE Annual Meeting and Conferences, Taipei, R.O.C. 

  • J. Chen and K.-P. Wang,  Designing Optimal Operation Profiles of Batch Reactors with the Integration of Function Approximation and Experimental Design, AIChE Annual Meeting, 2003, San Francisco, U.S.A. 

  • K.-P. Wang, J. Chen, S.-L. Lee and J.-Y. Houng,  Optimization of the Operating  pH Profile in a Batch Reactor for Asymmetric Bioreduction  of Ethyl 4-Chloro Acetoacetate, 8th Biochemical Engineering Conference, June, 2003, Kaohsiung, R.O.C.

  • Y. Yea and J. Chen, QDMC on the Basis of Neural Network Models in Nonlinear Processes,  2003 Chinese Automatic Control Conference, 781-786, March 2003, Chung-Li, R.O.C.

  • J. Chen and J.-H. Yen, Development of Dynamic PARAFAC for On-Line Batch Process Monitoring, PSE Asia 2002, 9-18, Taipei, Taiwan.

  • J. Chen and J.-H. Yen, Comparison of MPCA and PARAFAC for Batch Process Monitoring, AIChE Annual Meeting, 2002, Indianapolis, Indiana, U.S.A.

  • J. Chen and Y. Yea, Development of Neural Network Model Predictive Control for Multivariable Systems, Symposium on Computer Process Control, 59-68, 2001, Taipei, R.O.C.

  • J. Chen and R-G. Sheui “Optimal Trajectory Design in Batch Processes Using Soft Computing,” AIChE Annual Meeting, 2001, Reno, NV, U.S.A.

  • J. Chen,  K.-C. Liu and J.-H. Yen “On-Line Batch Process Monitoring,” Global Chinese Petroleum and Petrochemical Technology Symposium, 2001, R.O.C.  

  • J. Chen and J. Liu, Multivariate Calibration Models Based on Functional Space and Partial Least Square for Batch Processes IFAC-CHEMFAS-4, 161-166, 2001, Jejudo Island, Korea.

  • Y. Yea and J. Chen, Pole Placement Design Based on Instantaneous Linearization of Neural Networks 2001 Chinese Automatic Control Conference, Vol I, 266-271, March 2001, Tao-Yuan, R.O.C.

  • J. Chen, Q. Liu and C. Wang, Mixture PCA Network for Process Monitoring and Diagnosis, Proceedings of the 2000 CIChE Annual Meeting and Conferences, 93-96, 2000, Taipei, R.O.C.

  • J. Chen and J. Liu, On-Line Piecewise Monitoring for Batch Process, IFAC - ADCHEM 2000. Vol. I, 647-652, June 2000, Pisa, Italy.

  • J. Chen and Y. Yea, Neural Network Model Predictive Control on Multivariable Systems, 2000 Chinese Automatic Control Conference, Vol I, 498-503, March 2000, Hsin-Chu, R.O.C.

  • J. Chen and J. Liu, Process Monitoring Using Principal Component Analysis in Different Operating Time Processes, 1999 IFAC World Congress, Vol. N, 91-96, July 1999, Beijing, China.

  • J. Chen, M. Subramaniam and S.-S. Jang, Optimal Design Using Neural Network and Information Analysis in Plasma Etching,3rd Taipei-Kyushu Joint Symposium on Chemical Engineering, 1999, Taipei, R.O.C.

  • J. Chen, Y. Yea and T. Huang, Parallel Algorithm for Training MLP Neural Network, Symposium on Computer Process Control, 260-267, 1999, Taipei, R.O.C.

  • 劉佳霖, 陳榮輝, 黃天志, 陸木榮, 連鑄製程表面缺陷的監督方法, Symposium on Computer Process Control, 37-46, 1999, Taipei, R.O.C.

  • J. Chen, C. Liao and J. Liu, Batch Process Analyzing and Monitoring Us-ing Functional Space Analysis and Principal Component Analysis, Proceedings of the 1999 CIChE Annual Meeting and Conferences, 265-268, 1999, Kaoshiung, R.O.C.

  • 劉佳霖, 陳榮輝, 鍾進煌, 王一虹, 應用多變量統計程序控制於脫水塔異常偵測, Symposium on Computer Process Control, 72-78, Dec. 1998, Taipei, R.O.C.

  • J. Chen and J. Liu, Application of Multivariate Statistic Process Control in Different Operating Time Processes Symposium on Computer  Process Control, 19-28, Dec. 1997, Taipei, R.O.C. 

  • J. J. Lin, H.-S. You, J. Liu and J. Chen, Detecting Abnormal Events via Real-Time Process Safety Monitoring System, International Section of the ISSA for Prevention of Occupational Risks in the Chemical Industry, June 1997,  Frankfurt, Germany.

  • J. Chen, D. S. H. Wong, S.-S. Jang and S-L Yang, Nonlinear Experimental Design Using Artificial Intelligence, Symposium on Computer Process Control, 184-194, Dec. 1996, Taipei, R.O.C. 

  • 林正鄰, 游輝祥, 劉佳霖, 陳榮輝, 應用類神經網路在化工製程錯誤診斷之研究, Symposium on Computer Process Control, 128-134,Dec. 1996, Taipei, R.O.C. 

  • J. Chen, D. S. H. Wong and S.-S. Jang, Optimal Process Design Using Neural Network, Hybrid Search and Clustering Analysis, AIChE Annual Meeting, Nov. 1996, Chicago, IL, U.S.A.

  • J. Chen, Approximation of Nonlinear System Using WaveARX Neural Network, Symposium on Computer Process Control, 38-51, Dec. 1995, Taipei, R.O.C.

  • J. Chen and D. D. Bruns, System Identification Using WaveARX Neural Network, AIChE Annual Meeting, Nov. 1995, Miami Beach, FL, U.S.A.

  • 吳慶洋, 陳榮輝, 發展主動學習挖掘出歷史數據機制以有效建立動態虛擬量測元件, 化工 (The Chin. I. Ch. E.), 65(2), 45-63, 2018.

  • P. Sun, J. Chen, L. Xie, Self-Active and Recursively Selective Gaussian Process Models for Nonlinear Distributed Parameter Systems, Dynamics and Control of Process Systems, Ed. Wen, C.; Long, X. et al., Auris Reference Limite, 2015.

  • 陳榮輝 由大數據至智慧工業製造的數據分析與應用, 化工(The Chin. I. Ch. E.) 62(3) 77-89, 2015

  • J. Chen and  Y.-C. Cheng, Using Neural Networks and PLS to Design Multi-loop PID Controllers in Nonlinear MIMO Processes, Advances in the Dynamics, Instrumentation and Control, Ed. C. Y. Su, S. Rakheja, E. Wang, R. B. Bhat, World Scientific Press, 2004.

  • 陳榮輝 發展PCA類神經網路於錯誤診斷,” 工程科技通訊 (Engineering Science & Technology Bulletin, NSC), 47, 49-52, 2000

  • 陳榮輝, 劉佳霖 應用化學計量於程序監督與預測,” 化工 (The Chin. I. Ch. E.), 45(3), 28-36,1998.

  • 莊晴雯,Kernel子空間方法的Hammerstein系統辨識於開迴路下的正規採樣數據及閉迴路下的過採樣數據, Sept., 2022.

  • 黃世傑,發展由單步至多步的動態概率品質預測模型, July, 2022.

  • 張詠詞,發展深度模型的圖像/影像監控系統於工業上的應用, Jan., 2021.

  • 李宜珊,利用多品別與異常數據資訊以開發新型的VAE監控模型, July. 2020.

  • 侯冠宇,發展基於小波函數的PLS模型用於批次製程的品質監控, June. 2020.

  • 陳俊龍,開發半監督VAE/GAN模型於非線性靜態與動態程序的軟測量, June. 2020.

  • 吳慶洋,使用主動式數據選擇改進潛變數的軟測量模型, July. 2016.

  • 古紹武,連續時變系統之辨識與其控制性能評估,July. 2016.

  • 莊英譽,基於模型的大規模系統數據校正與參數估計,Jan. 2015.

  • 周宸霈,數據選擇的高斯過程模型於薄膜過濾程序的建模及其疊代學習控制,Jan. 2015.

  • Lester L. T. Chen (博士論文), 高斯程序於模型辨識,控制與效能評估:數據選擇以改善模型不確定性,Jan. 2014.

  • 黃皓芳,LQG基準控制器性能評估於線性時變系統,July. 2014.

  • 何忠儒,透過膜接觸器新製程改善二氧化碳捕捉之能源效率,Jul. 2013.

  • 黃家瑜,應用紋理分析於超音波影像以增強監控與診斷薄膜過濾,Jul. 2013.

  • 彭勇志,應用訊息熵在數據校正,Jan. 2013.

  • 許盛榮, 變壓吸附法的學習控制於放射線氪及氙氣的純化設計,Jan. 2013.

  • Jose C. Munoz (博士論文), 發展以相關信息熵為基礎的數據建模,數據校正及控制器設計,Jul.  2012.

  • 楊昀臻,應用超聲波於監控與診斷膜分離程序,Jan. 2011.

  • 張育翔,發展火焰影相技術以提昇燃燒控制迴路的效能,Jan. 2011.

  • 林昱宏,重覆性程序的預測控制及其性能評估與診斷,Jul. 2010.

  • 朱志強,結合決定性與隨機性之模式基礎控制的數據導向逐批控制器於具有隨機分佈特性之產品製程,Jul. 2009.

  • 顏士揚,膜管分離器結合預反應器於生質柴油製程之模擬與實驗驗證,Jul. 2009.

  • 宋哲銘,以IOHMM為基礎的MPLS模式於線上批次製程監控,Jan. 2009.

  • 江衍澄,HSMM為基礎的錯誤診斷於批次操作系統,Jan. 2009.

  • 劉凱永,以SVM-PLS模式為基礎的控制策略應用於多產品多機台之製程,Jan. 2009.

  • 王韋硯,以PCA為基礎的多變數系統效能評估,Jul. 2008.

  • 鄭雅方,薄膜分離純化生質柴油及其相圖之研究,Jul. 2008.

  • 陳明輝,疊代學習策略於模擬移動床參數估算與操作設計,Jul. 2008.

  • 康晁愷,批次單元疊代式學習控制的效能評估,Jul. 2007.

  • 吳秉鍾,以中空纖維薄膜蒸餾模組於去鹽製程:建模與最適化設計,Jul. 2007.

  • 謝凱珽,用於模擬移動床之PLS為基礎的週期間與週期內的控制策略,Jul. 2007.

  • 蔡仁凱,比較多站式製程之MPLS與MBPLS為基礎的控制設計,Jul. 2007.

  • 周國棟,用於批次單元之數據為基礎的疊代式學習控制,Jul. 2007.

  • 許家榮,自我成長的隱藏式馬可夫樹在製程監控之應用,Jan. 2007.

  • 林昆祺,以MPLS的模式結構進行最後產品品質之批次間與本批次間的控制,Jul.  2006.

  • 葉育志 (博士論文),控制系統之效能監控與失誤診斷,Jun.  2005.

  • 王凡,以PLS為基礎的dEWMA控制器於多變數半導體製程之研究,July  2005.

  • 陳信宏,發展隱藏式馬可夫樹模式之即時批次監控系統,Jun.  2005.

  • 何雲鵬,以碎形編碼與小波轉換為基礎之批次監控系統,Jul.  2005.

  • 張旺榮,利用隱藏馬可夫樹模式以提昇製程監控效能,Jul. 2004. 

  • 黃順祺,串聯式與並聯式的串級控制環路效能評估,Jul. 2004. 

  • 王冠博,利由混合式函數近似與實驗設計法於批次操作軌跡的設計,Jul. 2003.

  • 鄭逸群,動態PLS模式結構下進行線性及非線性多變數控制器的線上調適,Jul. 2003.

  • 黃天志, 利用類神經網路進行線上自我調整PID控制器之設計,Jul. 2002.

  • 嚴任宏,發展PARAFAC離線及線上批次製程監控系統,Jul. 2002.

  • 劉坤志,線上即時批次製程監控 ,Jul. 2001.

  • 王志偉,含未知擾動之非線性系統類神經網路模式預測控制的設計, Jul. 2001.

  • 薛榮貴,批次製程最適操作軌跡之實驗設計,Jul. 2001.

  • 葉育志 , 多變數類神經網路模式預測控制的設計,Jul. 2000.

  • 廖建茂 , 含記憶功能的主成分分析監控系統  Jul. 2000.

  • 陳維弘 , 異丙醇、環己烷與水三成份非均勻相共沸蒸餾系統之分析與控制,Jul. 1999.

  • 鐘立人 , 應用多變數主要組成因素分析於蒸餾塔操作系統,Jul. 1999.

  •