Junghui Chen
Orcid: 0000-0002-9994-839X
According to our database1,
Junghui Chen
authored at least 49 papers
between 2005 and 2024.
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Bibliography
2024
Prognostics for Semiconductor Sustainability: Tool Failure Behavior Prediction in Fabrication Processes.
IEEE Trans. Syst. Man Cybern. Syst., June, 2024
A Priori Knowledge-Based Dual Hierarchical RNN for Spatial-Temporal Process Modeling: Using a Multitubular Reactor as a Case Study.
IEEE Trans. Ind. Informatics, January, 2024
A mixture of shallow neural networks for virtual sensing: Could perform better than deep neural networks.
Expert Syst. Appl., 2024
Automatic segmentation of dynamic and static models based on high order slow feature analysis and principal component analysis for multiphase batch monitoring.
Expert Syst. Appl., 2024
A robust semi-supervised learning scheme for development of within-batch quality prediction soft-sensors.
Eng. Appl. Artif. Intell., 2024
Facilitating Reinforcement Learning for Process Control Using Transfer Learning: Perspectives.
CoRR, 2024
A concise subspace projection based meta-learning method for fast modeling and monitoring in multi-grade semiconductor process.
Comput. Ind. Eng., 2024
A novel semi-supervised robust learning framework for dynamic generative latent variable models and its application to industrial virtual metrology.
Adv. Eng. Informatics, 2024
A Fast Predictive Control Method for Vehicle Path Tracking Based on a Recurrent Neural Network.
IEEE Access, 2024
2023
Accelerating reinforcement learning with case-based model-assisted experience augmentation for process control.
Neural Networks, January, 2023
Deep Learning-Based Binocular Image Analysis for In Situ Measurement of Particle Length Distribution During Crystallization Process.
IEEE Trans. Instrum. Meas., 2023
In Situ Measurement of 2-D Crystal Size Distribution During Cooling Crystallization Process via a Binocular Telecentric Imaging System.
IEEE Trans. Instrum. Meas., 2023
Surrogate Empowered Sim2Real Transfer of Deep Reinforcement Learning for ORC Superheat Control.
CoRR, 2023
Comput. Chem. Eng., 2023
2022
Deep Neural Network-Embedded Stochastic Nonlinear State-Space Models and Their Applications to Process Monitoring.
IEEE Trans. Neural Networks Learn. Syst., 2022
Establishing Convolutional Neural Network Kalman Recurrent Variational Autoencoder Using Infrared Imaging for Process Monitoring: An Application in Spinning Disk Processes.
IEEE Trans. Instrum. Meas., 2022
Variational PLS-Based Calibration Model Building With Semi-Supervised Learning for Moisture Measurement During Fluidized Bed Drying by NIR Spectroscopy.
IEEE Trans. Instrum. Meas., 2022
Developing a Conditional Variational Autoencoder to Guide Spectral Data Augmentation for Calibration Modeling.
IEEE Trans. Instrum. Meas., 2022
Using source data to aid and build variational state-space autoencoders with sparse target data for process monitoring.
Neural Networks, 2022
Performance assessment for non-Gaussian systems by minimum entropy control and dynamic data reconciliation.
J. Frankl. Inst., 2022
Enhancing Monitoring Performance of Pharmaceutical Processes Using Dual-Attention Latent Dynamic Conditional State-Space Model.
Proceedings of the 13th Asian Control Conference, 2022
2021
Semi-Supervised Learning-Based Calibration Model Building of NIR Spectroscopy for In Situ Measurement of Biochemical Processes Under Insufficiently and Inaccurately Labeled Samples.
IEEE Trans. Instrum. Meas., 2021
Supervised and semi-supervised probabilistic learning with deep neural networks for concurrent process-quality monitoring.
Neural Networks, 2021
Statistical information based two-layer model predictive control with dynamic economy and control performance for non-Gaussian stochastic process.
J. Frankl. Inst., 2021
Dual-layer feature extraction based soft sensor methods and applications to industrial polyethylene processes.
Comput. Chem. Eng., 2021
2020
Deep Learning of Complex Batch Process Data and Its Application on Quality Prediction.
IEEE Trans. Ind. Informatics, 2020
Functional Soft Sensor Based on Spectra Data for Predicting Multiple Quality Variables.
IEEE Access, 2020
Prognostics of tool failing behavior based on autoassociative Gaussian process regression for semiconductor manufacturing.
Proceedings of the 2020 IEEE International Conference on Industrial Technology, 2020
Diagnosis of Nonlinearity-induced Oscillations in Process Control Loops Based on Adaptive Chirp Mode Decomposition.
Proceedings of the 2020 American Control Conference, 2020
2019
Performance Analysis of Dynamic PCA for Closed-Loop Process Monitoring and Its Improvement by Output Oversampling Scheme.
IEEE Trans. Control. Syst. Technol., 2019
Development of Self-Learning Kernel Regression Models for Virtual Sensors on Nonlinear Processes.
IEEE Trans Autom. Sci. Eng., 2019
Concurrent Fault Detection and Anomaly Location in Closed-Loop Dynamic Systems With Measured Disturbances.
IEEE Trans Autom. Sci. Eng., 2019
Enhancing performance of generalized minimum variance control via dynamic data reconciliation.
J. Frankl. Inst., 2019
Systematic Development of a New Variational Autoencoder Model Based on Uncertain Data for Monitoring Nonlinear Processes.
IEEE Access, 2019
Proceedings of the 12th Asian Control Conference, 2019
Proceedings of the 12th Asian Control Conference, 2019
2018
A new excitation scheme for closed-loop subspace identification using additional sampling outputs and its extension to instrumental variable method.
J. Frankl. Inst., 2018
Fault diagnosis for processes with feedback control loops by shifted output sampling approach.
J. Frankl. Inst., 2018
Development of Decay Based PLS Model and Its Economic Run-to-Run Control for Semiconductor Processes.
Proceedings of the 2018 Annual American Control Conference, 2018
2017
Probabilistic uncertainty based simultaneous process design and control with iterative expected improvement model.
Comput. Chem. Eng., 2017
Soft sensors of nonlinear industrial processes based on self-learning kernel regression model.
Proceedings of the 11th Asian Control Conference, 2017
2016
IEEE Trans. Ind. Informatics, 2016
Single Neuron Stochastic Predictive PID Control Algorithm for Nonlinear and Non-Gaussian Systems Using the Survival Information Potential Criterion.
Entropy, 2016
2015
Correntropy based data reconciliation and gross error detection and identification for nonlinear dynamic processes.
Comput. Chem. Eng., 2015
2014
Simultaneous data reconciliation and gross error detection for dynamic systems using particle filter and measurement test.
Comput. Chem. Eng., 2014
2009
Proceedings of the CSIE 2009, 2009 WRI World Congress on Computer Science and Information Engineering, March 31, 2009
2006
Intelligent Experimental Design Using an Artificial Neural Network Meta Model and Information Theory.
Proceedings of the Integrated Intelligent Systems for Engineering Design, 2006
2005
Proceedings of the American Control Conference, 2005