Review of Recent Research on Data-Based Process Monitoring von Ge, Zhiqiang, Song, Zhihuan, Gao, Furong

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Distributed Parallel PCA for Modeling and Monitoring of Large-Scale Plant-Wide Processes With Big Data von Zhu, Jinlin, Ge, Zhiqiang, Song, Zhihuan

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A Probabilistic Just-in-Time Learning Framework for Soft Sensor Development With Missing Data von Yuan, Xiaofeng, Ge, Zhiqiang, Huang, Biao, Song, Zhihuan

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Weighted Linear Dynamic System for Feature Representation and Soft Sensor Application in Nonlinear Dynamic Industrial Processes von Yuan, Xiaofeng, Wang, Yalin, Yang, Chunhua, Ge, Zhiqiang, Song, Zhihuan, Gui, Weihua

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Locally Weighted Kernel Principal Component Regression Model for Soft Sensing of Nonlinear Time-Variant Processes von Yuan, Xiaofeng, Ge, Zhiqiang, Song, Zhihuan

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Data Mining and Analytics in the Process Industry: The Role of Machine Learning von Ge, Zhiqiang, Song, Zhihuan, Ding, Steven X., Huang, Biao

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Mixture Bayesian regularization method of PPCA for multimode process monitoring von Ge, Zhiqiang, Song, Zhihuan

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Real-Time Forecasting of Subsurface Inclusion Defects for Continuous Casting Slabs: A Data-Driven Comparative Study von Wei, Chihang, Song, Zhihuan

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A comparative study of just-in-time-learning based methods for online soft sensor modeling von Ge, Zhiqiang, Song, Zhihuan

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Semisupervised JITL Framework for Nonlinear Industrial Soft Sensing Based on Locally Semisupervised Weighted PCR von Yuan, Xiaofeng, Ge, Zhiqiang, Huang, Biao, Song, Zhihuan, Wang, Yalin

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Deep Learning of Complex Batch Process Data and Its Application on Quality Prediction von Wang, Kai, Gopaluni, Ratna Bhushan, Chen, Junghui, Song, Zhihuan

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Process Monitoring Based on Independent Component Analysis−Principal Component Analysis (ICA−PCA) and Similarity Factors von Ge, Zhiqiang, Song, Zhihuan

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Autoregressive Dynamic Latent Variable Models for Process Monitoring von Le Zhou, Gang Li, Zhihuan Song, Qin, S. Joe

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Variational Bayesian Gaussian Mixture Regression for Soft Sensing Key Variables in Non-Gaussian Industrial Processes von Zhu, Jinlin, Ge, Zhiqiang, Song, Zhihuan

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Semisupervised Bayesian method for soft sensor modeling with unlabeled data samples von Ge, Zhiqiang, Song, Zhihuan

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Multimode process monitoring based on Bayesian method von Ge, Zhiqiang, Song, Zhihuan

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Global–Local Structure Analysis Model and Its Application for Fault Detection and Identification von Zhang, Muguang, Ge, Zhiqiang, Song, Zhihuan, Fu, Ruowei

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HMM-Driven Robust Probabilistic Principal Component Analyzer for Dynamic Process Fault Classification von Zhu, Jinlin, Ge, Zhiqiang, Song, Zhihuan

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Mixture semisupervised principal component regression model and soft sensor application von Ge, Zhiqiang, Huang, Biao, Song, Zhihuan

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Online monitoring of nonlinear multiple mode processes based on adaptive local model approach von Ge, Zhiqiang, Song, Zhihuan

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