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ORCIDJunghui Chen
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2020 – today
- 2024
[j37]Xialai Wu, Ling Lin, Junghui Chen
, Shuxin Du:
A Fast Predictive Control Method for Vehicle Path Tracking Based on a Recurrent Neural Network. IEEE Access 12: 141104-141115 (2024)- [j36]Wenxue Han, Weiming Shao, Chihang Wei, Wei Song, Can Chen, Junghui Chen:
A novel semi-supervised robust learning framework for dynamic generative latent variable models and its application to industrial virtual metrology. Adv. Eng. Informatics 62: 102775 (2024) - [j35]Jingxiang Liu, Weimin Zhu, Guoqing Mu, Chun-I Chen, Junghui Chen:
A concise subspace projection based meta-learning method for fast modeling and monitoring in multi-grade semiconductor process. Comput. Ind. Eng. 188: 109914 (2024) - [j34]Yi Shan Lee, Junghui Chen:
A robust semi-supervised learning scheme for development of within-batch quality prediction soft-sensors. Eng. Appl. Artif. Intell. 133: 107920 (2024) - [j33]Jingxiang Liu, Pin-Hsun Chen, Junghui Chen:
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. 248: 123271 (2024) - [j32]Weiming Shao, Xu Li, Yupeng Xing, Junghui Chen:
A mixture of shallow neural networks for virtual sensing: Could perform better than deep neural networks. Expert Syst. Appl. 256: 124870 (2024) - [j31]Pei Sun, Junghui Chen, Haoyi Que:
A Priori Knowledge-Based Dual Hierarchical RNN for Spatial-Temporal Process Modeling: Using a Multitubular Reactor as a Case Study. IEEE Trans. Ind. Informatics 20(1): 899-910 (2024) - [j30]Li Zhu, Junghui Chen, Chun-I Chen:
Prognostics for Semiconductor Sustainability: Tool Failure Behavior Prediction in Fabrication Processes. IEEE Trans. Syst. Man Cybern. Syst. 54(6): 3450-3460 (2024) - [i2]Runze Lin, Junghui Chen, Lei Xie, Hongye Su, Biao Huang:
Facilitating Reinforcement Learning for Process Control Using Transfer Learning: Perspectives. CoRR abs/2404.00247 (2024) - 2023
- [j29]Jingxiang Liu, Guoqing Mu, Junghui Chen:
Tensor slow feature analysis and its applications for batch process monitoring. Comput. Chem. Eng. 173: 108207 (2023) - [j28]Runze Lin, Junghui Chen, Lei Xie, Hongye Su:
Accelerating reinforcement learning with case-based model-assisted experience augmentation for process control. Neural Networks 158: 197-215 (2023) - [j27]Ji Fan, Tao Liu, Yan Huo, Yonghong Tan, Junghui Chen:
In Situ Measurement of 2-D Crystal Size Distribution During Cooling Crystallization Process via a Binocular Telecentric Imaging System. IEEE Trans. Instrum. Meas. 72: 1-15 (2023) - [j26]Ji Fan, Tao Liu, Yongcan Shuang, Bo Song, Junghui Chen, Yonghong Tan:
Deep Learning-Based Binocular Image Analysis for In Situ Measurement of Particle Length Distribution During Crystallization Process. IEEE Trans. Instrum. Meas. 72: 1-14 (2023) - [i1]Runze Lin, Yangyang Luo, Xialai Wu, Junghui Chen, Biao Huang, Lei Xie, Hongye Su:
Surrogate Empowered Sim2Real Transfer of Deep Reinforcement Learning for ORC Superheat Control. CoRR abs/2308.02765 (2023) - 2022
- [j25]Mifeng Ren, Wen Zhang, Junghui Chen, Peng Shi, Gaowei Yan:
Performance assessment for non-Gaussian systems by minimum entropy control and dynamic data reconciliation. J. Frankl. Inst. 359(8): 3930-3950 (2022) - [j24]Yi Shan Lee, Junghui Chen:
Using source data to aid and build variational state-space autoencoders with sparse target data for process monitoring. Neural Networks 154: 455-468 (2022) - [j23]Guoqing Mu, Junghui Chen:
Developing a Conditional Variational Autoencoder to Guide Spectral Data Augmentation for Calibration Modeling. IEEE Trans. Instrum. Meas. 71: 1-8 (2022) - [j22]Guoqing Mu, Tao Liu, Junghui Chen, Chao Shang, Chongquan 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: 1-13 (2022) - [j21]Yongci Zhang, Yi Shan Lee, Huanting Lin, Junghui Chen:
Establishing Convolutional Neural Network Kalman Recurrent Variational Autoencoder Using Infrared Imaging for Process Monitoring: An Application in Spinning Disk Processes. IEEE Trans. Instrum. Meas. 71: 1-12 (2022) - [j20]Kai Wang, Junghui Chen, Zhihuan Song, Yalin Wang, Chunhua Yang:
Deep Neural Network-Embedded Stochastic Nonlinear State-Space Models and Their Applications to Process Monitoring. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7682-7694 (2022) - [c9]Yi Shan Lee, Junghui Chen:
Enhancing Monitoring Performance of Pharmaceutical Processes Using Dual-Attention Latent Dynamic Conditional State-Space Model. ASCC 2022: 227-232 - 2021
- [j19]Jingxiang Liu, Jie Hou, Junghui Chen:
Dual-layer feature extraction based soft sensor methods and applications to industrial polyethylene processes. Comput. Chem. Eng. 154: 107469 (2021) - [j18]Mifeng Ren, Junghui Chen, Peng Shi, Gaowei Yan, Lan Cheng:
Statistical information based two-layer model predictive control with dynamic economy and control performance for non-Gaussian stochastic process. J. Frankl. Inst. 358(4): 2279-2300 (2021) - [j17]Qiming Chen, Junghui Chen, Xun Lang, Lei Xie, Naveed ur Rehman, Hongye Su:
Self-tuning variational mode decomposition. J. Frankl. Inst. 358(15): 7825-7862 (2021) - [j16]Kai Wang, Xiaofeng Yuan, Junghui Chen, Yalin Wang:
Supervised and semi-supervised probabilistic learning with deep neural networks for concurrent process-quality monitoring. Neural Networks 136: 54-62 (2021) - [j15]Guoqing Mu, Tao Liu, Chuang Xue, Junghui Chen:
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. 70: 1-12 (2021) - 2020
- [j14]Jingxiang Liu, Dan Wang, Junghui Chen, Jie Hou:
Functional Soft Sensor Based on Spectra Data for Predicting Multiple Quality Variables. IEEE Access 8: 160355-160362 (2020) - [j13]Kai Wang, R. Bhushan Gopaluni, Junghui Chen, Zhihuan Song:
Deep Learning of Complex Batch Process Data and Its Application on Quality Prediction. IEEE Trans. Ind. Informatics 16(12): 7233-7242 (2020) - [c8]Qiming Chen, Junghui Chen, Xun Lang, Lei Xie, Chenglong Jiang, Hongye Su:
Diagnosis of Nonlinearity-induced Oscillations in Process Control Loops Based on Adaptive Chirp Mode Decomposition. ACC 2020: 2772-2777 - [c7]Li Zhu, Junghui Chen, Chun-I Chen:
Prognostics of tool failing behavior based on autoassociative Gaussian process regression for semiconductor manufacturing. ICIT 2020: 316-321
2010 – 2019
- 2019
- [j12]Kai Wang, Michael G. Forbes, R. Bhushan Gopaluni, Junghui Chen, Zhihuan Song:
Systematic Development of a New Variational Autoencoder Model Based on Uncertain Data for Monitoring Nonlinear Processes. IEEE Access 7: 22554-22565 (2019) - [j11]Zhengjiang Zhang, Junghui Chen:
Enhancing performance of generalized minimum variance control via dynamic data reconciliation. J. Frankl. Inst. 356(15): 8829-8854 (2019) - [j10]Chihang Wei, Junghui Chen, Zhihuan Song, Chun-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) - [j9]Kai Wang, Junghui Chen, Zhihuan 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) - [j8]Kai Wang, Junghui Chen, Zhihuan 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) - [c6]Lester Lik Teck Chan, Junghui Chen:
Reducing Cost of Process Modeling through Multi-source Data Transfer Learning. ASCC 2019: 474-479 - [c5]Kai Wang, Junghui Chen, Zhihuan Song:
Fault Detection Based on Variational Autoencoders for Complex Nonlinear Processes. ASCC 2019: 1352-1357 - 2018
- [j7]Kai Wang, Junghui Chen, Zhihuan Song:
Fault diagnosis for processes with feedback control loops by shifted output sampling approach. J. Frankl. Inst. 355(7): 3249-3273 (2018) - [j6]Kai Wang, Junghui Chen, Zhihuan Song:
A new excitation scheme for closed-loop subspace identification using additional sampling outputs and its extension to instrumental variable method. J. Frankl. Inst. 355(14): 6675-6692 (2018) - [c4]Pengcheng Lu, Junghui Chen, Lei Xie:
Development of Decay Based PLS Model and Its Economic Run-to-Run Control for Semiconductor Processes. ACC 2018: 6469-6474 - 2017
- [j5]Lester Lik Teck Chan, Junghui Chen:
Probabilistic uncertainty based simultaneous process design and control with iterative expected improvement model. Comput. Chem. Eng. 106: 609-620 (2017) - [c3]Chihang Wei, Junghui Chen, Zhihuan Song, Chun-I Chen:
Soft sensors of nonlinear industrial processes based on self-learning kernel regression model. ASCC 2017: 1783-1788 - 2016
- [j4]Mifeng Ren, Ting Cheng, Junghui Chen, Xinying Xu, Lan Cheng:
Single Neuron Stochastic Predictive PID Control Algorithm for Nonlinear and Non-Gaussian Systems Using the Survival Information Potential Criterion. Entropy 18(6): 218 (2016) - [j3]Zhiqiang Ge, Junghui Chen:
Plant-Wide Industrial Process Monitoring: A Distributed Modeling Framework. IEEE Trans. Ind. Informatics 12(1): 310-321 (2016) - 2015
- [j2]Zhengjiang Zhang, Junghui Chen:
Correntropy based data reconciliation and gross error detection and identification for nonlinear dynamic processes. Comput. Chem. Eng. 75: 120-134 (2015) - 2014
- [j1]Zhengjiang Zhang, Junghui Chen:
Simultaneous data reconciliation and gross error detection for dynamic systems using particle filter and measurement test. Comput. Chem. Eng. 69: 66-74 (2014)
2000 – 2009
- 2009
- [c2]Junghui Chen, Ren-Kai Tsai:
Development of MBPLS Based Control for Serial Operation Processes. CSIE (4) 2009: 521-525 - 2006
- [p1]Shi-Shang Jang, David Shan-Hill Wong, Junghui Chen:
Intelligent Experimental Design Using an Artificial Neural Network Meta Model and Information Theory. Integrated Intelligent Systems for Engineering Design 2006: 258-273 - 2005
- [c1]Junghui Chen, Yuezhi Yea:
Assessment and diagnosis of feedforward/feedback control system. ACC 2005: 490-495vol.1
Coauthor Index
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