Zhi-qiang Ge
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Zhi-qiang Geengineering Degrees
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Industrial Engineering
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Engineering
Zhi-qiang Ge's Degrees
- Bachelors Industrial Engineering Tsinghua University
Why Is Zhi-qiang Ge Influential?
(Suggest an Edit or Addition)Zhi-qiang Ge's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Review of Recent Research on Data-Based Process Monitoring (2013) (739)
- Data Mining and Analytics in the Process Industry: The Role of Machine Learning (2017) (580)
- Review on data-driven modeling and monitoring for plant-wide industrial processes (2017) (404)
- Process Monitoring Based on Independent Component Analysis - Principal Component Analysis ( ICA - PCA ) and Similarity Factors (2007) (254)
- Improved kernel PCA-based monitoring approach for nonlinear processes (2009) (189)
- Deep Learning of Semisupervised Process Data With Hierarchical Extreme Learning Machine and Soft Sensor Application (2018) (184)
- Distributed Parallel PCA for Modeling and Monitoring of Large-Scale Plant-Wide Processes With Big Data (2017) (179)
- Distributed PCA Model for Plant-Wide Process Monitoring (2013) (175)
- A comparative study of just-in-time-learning based methods for online soft sensor modeling (2010) (168)
- Process Data Analytics via Probabilistic Latent Variable Models: A Tutorial Review (2018) (163)
- Online monitoring of nonlinear multiple mode processes based on adaptive local model approach (2008) (153)
- Review and big data perspectives on robust data mining approaches for industrial process modeling with outliers and missing data (2018) (149)
- Mixture Bayesian regularization method of PPCA for multimode process monitoring (2010) (135)
- Nonlinear process monitoring based on linear subspace and Bayesian inference (2010) (132)
- Global–Local Structure Analysis Model and Its Application for Fault Detection and Identification (2011) (126)
- Batch process monitoring based on support vector data description method (2011) (119)
- Locally Weighted Kernel Principal Component Regression Model for Soft Sensing of Nonlinear Time-Variant Processes (2014) (118)
- Weighted Linear Dynamic System for Feature Representation and Soft Sensor Application in Nonlinear Dynamic Industrial Processes (2018) (117)
- A Survey on Deep Learning for Data-Driven Soft Sensors (2021) (116)
- Multimode process monitoring based on Bayesian method (2009) (108)
- Semisupervised JITL Framework for Nonlinear Industrial Soft Sensing Based on Locally Semisupervised Weighted PCR (2017) (105)
- Mixture probabilistic PCR model for soft sensing of multimode processes (2011) (94)
- Soft sensor model development in multiphase/multimode processes based on Gaussian mixture regression (2014) (86)
- Plant-Wide Industrial Process Monitoring: A Distributed Modeling Framework (2016) (84)
- Semi-supervised fault classification based on dynamic Sparse Stacked auto-encoders model (2017) (84)
- A Probabilistic Just-in-Time Learning Framework for Soft Sensor Development With Missing Data (2017) (83)
- Mixture semisupervised principal component regression model and soft sensor application (2014) (82)
- Soft Sensor Modeling of Nonlinear Industrial Processes Based on Weighted Probabilistic Projection Regression (2017) (80)
- Semisupervised Bayesian method for soft sensor modeling with unlabeled data samples (2011) (79)
- Distributed predictive modeling framework for prediction and diagnosis of key performance index in plant-wide processes (2017) (77)
- Quality prediction for polypropylene production process based on CLGPR model (2011) (72)
- Big data quality prediction in the process industry: A distributed parallel modeling framework (2018) (72)
- Multimode Process Monitoring Based on Switching Autoregressive Dynamic Latent Variable Model (2018) (69)
- Semisupervised Kernel Learning for FDA Model and its Application for Fault Classification in Industrial Processes (2016) (66)
- Performance-driven ensemble learning ICA model for improved non-Gaussian process monitoring (2013) (65)
- HMM-Driven Robust Probabilistic Principal Component Analyzer for Dynamic Process Fault Classification (2015) (64)
- Large-scale plant-wide process modeling and hierarchical monitoring: A distributed Bayesian network approach (2017) (63)
- Semiconductor Manufacturing Process Monitoring Based on Adaptive Substatistical PCA (2010) (60)
- Robust modeling of mixture probabilistic principal component analysis and process monitoring application (2014) (60)
- Probabilistic Sequential Network for Deep Learning of Complex Process Data and Soft Sensor Application (2019) (58)
- Scalable Semisupervised GMM for Big Data Quality Prediction in Multimode Processes (2019) (57)
- Nonlinear probabilistic latent variable regression models for soft sensor application: From shallow to deep structure (2020) (57)
- Deep Learning for Industrial KPI Prediction: When Ensemble Learning Meets Semi-Supervised Data (2021) (55)
- Co-training partial least squares model for semi-supervised soft sensor development (2015) (54)
- Semi-supervised Fisher discriminant analysis model for fault classification in industrial processes (2014) (53)
- Data‐based linear Gaussian state‐space model for dynamic process monitoring (2012) (51)
- Locally Weighted Prediction Methods for Latent Factor Analysis With Supervised and Semisupervised Process Data (2017) (51)
- Adaptive soft sensors for quality prediction under the framework of Bayesian network (2018) (51)
- Fault detection in non-Gaussian vibration systems using dynamic statistical-based approaches (2010) (50)
- Variational Bayesian Gaussian Mixture Regression for Soft Sensing Key Variables in Non-Gaussian Industrial Processes (2017) (49)
- Dynamic Probabilistic Latent Variable Model for Process Data Modeling and Regression Application (2019) (49)
- Multivariate Statistical Process Control (2012) (49)
- Utilizing transition information in online quality prediction of multiphase batch processes (2012) (47)
- Robust Online Monitoring for Multimode Processes Based on Nonlinear External Analysis (2008) (47)
- Bagging support vector data description model for batch process monitoring (2013) (47)
- Maximum-likelihood mixture factor analysis model and its application for process monitoring (2010) (46)
- Analytic Hierarchy Process Based Fuzzy Decision Fusion System for Model Prioritization and Process Monitoring Application (2019) (46)
- Nonlinear feature extraction for soft sensor modeling based on weighted probabilistic PCA (2015) (45)
- Nonlinear semisupervised principal component regression for soft sensor modeling and its mixture form (2014) (45)
- Local ICA for multivariate statistical fault diagnosis in systems with unknown signal and error distributions (2012) (44)
- Non-Gaussian Industrial Process Monitoring With Probabilistic Independent Component Analysis (2017) (44)
- Two-dimensional Bayesian monitoring method for nonlinear multimode processes (2011) (43)
- Robust semi-supervised mixture probabilistic principal component regression model development and application to soft sensors (2015) (43)
- Moving window adaptive soft sensor for state shifting process based on weighted supervised latent factor analysis (2017) (43)
- Probabilistic latent variable regression model for process-quality monitoring (2014) (43)
- Probabilistic learning of partial least squares regression model: Theory and industrial applications (2016) (42)
- Time Neighborhood Preserving Embedding Model and Its Application for Fault Detection (2013) (42)
- Weighted random forests for fault classification in industrial processes with hierarchical clustering model selection (2018) (41)
- Robust supervised probabilistic principal component analysis model for soft sensing of key process variables (2015) (40)
- Active learning strategy for smart soft sensor development under a small number of labeled data samples (2014) (40)
- Nonlinear Soft Sensor Development Based on Relevance Vector Machine (2010) (39)
- Mixture Bayesian Regularization of PCR Model and Soft Sensing Application (2015) (39)
- Distributed parallel deep learning of Hierarchical Extreme Learning Machine for multimode quality prediction with big process data (2019) (38)
- Quality variable prediction for chemical processes based on semisupervised Dirichlet process mixture of Gaussians (2019) (37)
- Soft-Sensor Development for Processes With Multiple Operating Modes Based on Semisupervised Gaussian Mixture Regression (2019) (37)
- Online Updating Soft Sensor Modeling and Industrial Application Based on Selectively Integrated Moving Window Approach (2017) (37)
- Supervised Latent Factor Analysis for Process Data Regression Modeling and Soft Sensor Application (2016) (37)
- Semi-supervised PLVR models for process monitoring with unequal sample sizes of process variables and quality variables (2015) (37)
- K-means Bayes algorithm for imbalanced fault classification and big data application (2019) (35)
- Double locally weighted principal component regression for soft sensor with sample selection under supervised latent structure (2016) (35)
- Sensor fault identification and isolation for multivariate non-Gaussian processes (2009) (34)
- Supervised linear dynamic system model for quality related fault detection in dynamic processes (2016) (33)
- Ensemble independent component regression models and soft sensing application (2014) (32)
- Parallel Computing and SGD-Based DPMM For Soft Sensor Development With Large-Scale Semisupervised Data (2019) (32)
- Data Augmentation Classifier for Imbalanced Fault Classification (2021) (31)
- Multimode Dynamic Process Monitoring Based on Mixture Canonical Variate Analysis Model (2015) (31)
- Nonlinear industrial soft sensor development based on semi-supervised probabilistic mixture of extreme learning machines (2019) (31)
- Kernel Generalization of PPCA for Nonlinear Probabilistic Monitoring (2010) (31)
- Two-level multiblock statistical monitoring for plant-wide processes (2009) (31)
- Quality prediction and analysis for large-scale processes based on multi-level principal component modeling strategy (2014) (29)
- Spatio‐temporal adaptive soft sensor for nonlinear time‐varying and variable drifting processes based on moving window LWPLS and time difference model (2016) (29)
- Semisupervised Robust Modeling of Multimode Industrial Processes for Quality Variable Prediction Based on Student's t Mixture Model (2020) (29)
- Decision fusion systems for fault detection and identification in industrial processes (2015) (26)
- Nonlocal structure constrained neighborhood preserving embedding model and its application for fault detection (2015) (25)
- Ensemble semi-supervised Fisher discriminant analysis model for fault classification in industrial processes. (2019) (25)
- Nonlinear Probabilistic Monitoring Based on the Gaussian Process Latent Variable Model (2010) (25)
- Robust Self-Supervised Model and Its Application for Fault Detection (2017) (25)
- Auxiliary Information-Guided Industrial Data Augmentation for Any-Shot Fault Learning and Diagnosis (2021) (25)
- A distribution-free method for process monitoring (2011) (25)
- Supervised Nonlinear Dynamic System for Soft Sensor Application Aided by Variational Auto-Encoder (2020) (24)
- Local Parameter Optimization of LSSVM for Industrial Soft Sensing With Big Data and Cloud Implementation (2020) (24)
- Active probabilistic sample selection for intelligent soft sensing of industrial processes (2016) (23)
- SVM-tree and SVM-forest algorithms for imbalanced fault classification in industrial processes (2019) (23)
- Automatic Deep Extraction of Robust Dynamic Features for Industrial Big Data Modeling and Soft Sensor Application (2020) (22)
- Two-level PLS model for quality prediction of multiphase batch processes (2014) (22)
- Multirate Factor Analysis Models for Fault Detection in Multirate Processes (2019) (21)
- External analysis‐based regression model for robust soft sensing of multimode chemical processes (2014) (20)
- Virtual Sensing f-CaO Content of Cement Clinker Based on Incremental Deep Dynamic Features Extracting and Transferring Model (2021) (20)
- Multimode process data modeling: A Dirichlet process mixture model based Bayesian robust factor analyzer approach (2015) (20)
- Streaming parallel variational Bayesian supervised factor analysis for adaptive soft sensor modeling with big process data (2020) (20)
- Bayesian Just-in-Time Learning and Its Application to Industrial Soft Sensing (2020) (20)
- Hierarchical Bayesian Network Modeling Framework for Large-Scale Process Monitoring and Decision Making (2020) (20)
- Probabilistic combination of local independent component regression model for multimode quality prediction in chemical processes (2014) (20)
- Improved two-level monitoring system for plant-wide processes (2014) (20)
- Semi-supervised mixture of latent factor analysis models with application to online key variable estimation (2019) (20)
- Fuzzy decision fusion system for fault classification with analytic hierarchy process approach (2017) (20)
- A Novel Statistical-Based Monitoring Approach for Complex Multivariate Processes (2009) (19)
- Scalable learning and probabilistic analytics of industrial big data based on parameter server: Framework, methods and applications (2019) (18)
- Nonlinear quality prediction for multiphase batch processes (2012) (18)
- Gated Stacked Target-Related Autoencoder: A Novel Deep Feature Extraction and Layerwise Ensemble Method for Industrial Soft Sensor Application (2020) (18)
- Monitoring and prediction of big process data with deep latent variable models and parallel computing (2020) (18)
- Process monitoring based on factor analysis: Probabilistic analysis of monitoring statistics in presence of both complete and incomplete measurements (2015) (17)
- Robust Bayesian networks for low-quality data modeling and process monitoring applications (2020) (17)
- Robust monitoring and fault reconstruction based on variational inference component analysis (2011) (17)
- Nonlinear Gaussian Mixture Regression for Multimode Quality Prediction With Partially Labeled Data (2019) (17)
- Multirate Dynamic Process Monitoring Based on Multirate Linear Gaussian State-Space Model (2019) (16)
- Online Monitoring and Quality Prediction of Multiphase Batch Processes with Uneven Length Problem (2014) (16)
- Weighted Nonlinear Dynamic System for Deep Extraction of Nonlinear Dynamic Latent Variables and Industrial Application (2021) (16)
- Dynamic mutual information similarity based transient process identification and fault detection (2018) (16)
- Switching LDS-based approach for process fault detection and classification (2015) (16)
- Refining data-driven soft sensor modeling framework with variable time reconstruction (2020) (16)
- Bayesian Nonlinear Gaussian Mixture Regression and its Application to Virtual Sensing for Multimode Industrial Processes (2020) (15)
- Variable selection for nonlinear soft sensor development with enhanced Binary Differential Evolution algorithm (2018) (15)
- Cooperative Deep Dynamic Feature Extraction and Variable Time-Delay Estimation for Industrial Quality Prediction (2021) (14)
- Gaussian Discriminative Analysis aided GAN for imbalanced big data augmentation and fault classification (2020) (14)
- Phase adaptive RVM model for quality prediction of multiphase batch processes with limited modeling batches (2016) (14)
- Multivariate Trajectory-Based Local Monitoring Method for Multiphase Batch Processes (2015) (13)
- Recursive Mixture Factor Analyzer for Monitoring Multimode Time-Variant Industrial Processes (2016) (13)
- Semisupervised Bayesian Gaussian Mixture Models for Non-Gaussian Soft Sensor (2019) (12)
- Augmented Multidimensional Convolutional Neural Network for Industrial Soft Sensing (2021) (12)
- Batch process monitoring based on multilevel ICA-PCA (2008) (11)
- Dynamic mixture probabilistic PCA classifier modeling and application for fault classification (2015) (11)
- Multirate Partial Least Squares for Process Monitoring (2015) (11)
- Semi-supervised data modeling and analytics in the process industry: Current research status and challenges (2021) (11)
- Dynamic Bayesian network for robust latent variable modeling and fault classification (2020) (11)
- Supervised neighborhood preserving embedding for feature extraction and its application for soft sensor modeling (2016) (11)
- Bayesian robust linear dynamic system approach for dynamic process monitoring (2016) (11)
- Hierarchical Quality Monitoring for Large-Scale Industrial Plants With Big Process Data (2019) (11)
- Industrial Big Data Modeling and Monitoring Framework for Plant-Wide Processes (2021) (10)
- Distributed Gaussian mixture model for monitoring plant-wide processes with multiple operating modes (2018) (9)
- A Wavelet Transform-Assisted Convolutional Neural Network Multi-Model Framework for Monitoring Large-Scale Fluorochemical Engineering Processes (2020) (9)
- Improved Population-Based Incremental Learning of Bayesian Networks with partly known structure and parallel computing (2020) (9)
- Distributed model projection based transition processes recognition and quality-related fault detection (2016) (9)
- Dynamic Features Incorporated Locally Weighted Deep Learning Model for Soft Sensor Development (2021) (8)
- Bayesian inference and joint probability analysis for batch process monitoring (2013) (8)
- Subspace partial least squares model for multivariate spectroscopic calibration (2013) (8)
- Bayesian network for dynamic variable structure learning and transfer modeling of probabilistic soft sensor (2021) (8)
- Deep ensemble forests for industrial fault classification (2019) (7)
- A Nonlinear Probabilistic Method for Process Monitoring (2010) (7)
- Multi-rate principal component regression model for soft sensor application in industrial processes (2019) (7)
- Process-Quality Monitoring Using Semi-Supervised Probability Latent Variable Regression Models (2014) (7)
- Nonlinear fault detection based on locally linear embedding (2013) (7)
- Multiple Fault Detection Using Multi-rate Probability Principal Component Analysis Models (2017) (7)
- Information-Transfer PLS Model for Quality Prediction in Transition Periods of Batch Processes (2013) (7)
- Soft Sensor for Multiphase and Multimode Processes Based on Gaussian Mixture Regression (2014) (6)
- Statistical Prediction of Product Quality in Batch Processes with Limited Batch-Cycle Data (2012) (6)
- Self-Training Statistical Quality Prediction of Batch Processes with Limited Quality Data (2013) (6)
- Industrial Process Modeling and Fault Detection with Recurrent Kalman Variational Autoencoder (2020) (6)
- Dynamic ensemble selection based improved random forests for fault classification in industrial processes (2022) (6)
- Rethinking the Value of Just-in-Time Learning in the Era of Industrial Big Data (2021) (6)
- Weakly Supervised Multilayer Perceptron for Industrial Fault Classification With Inaccurate and Incomplete Labels (2022) (6)
- Industrial Virtual Sensing for Big Process Data Based on Parallelized Nonlinear Variational Bayesian Factor Regression (2020) (6)
- Nonlinear dynamic process monitoring based on kernel partial least squares (2012) (6)
- Quantum statistic based semi-supervised learning approach for industrial soft sensor development (2018) (5)
- Non-Gaussian Process Monitoring (2013) (5)
- Online batch process monitoring based on multi-model ICA-PCA method (2008) (5)
- Process monitoring based on generalized orthogonal neighborhood preserving embedding (2012) (4)
- Distributed Gaussian mixture model for monitoring multimode plant-wide process (2016) (4)
- Incorporating setting information for maintenance-free quality modeling of batch processes (2013) (4)
- Dynamic process monitoring based on probabilistic principle component regression (2013) (4)
- A recursively updated Map-Reduce based PCA for monitoring the time-varying fluorochemical engineering processes with big data (2020) (4)
- Adaptive monitoring for transition process using dynamic mutual information similarity analysis (2016) (4)
- Adaptive Soft Sensor Modeling Based on Weighted Supervised Latent Factor Analysis with Selectively Integrated Moving Windows (2017) (3)
- JITL based local monitoring method for transitions of multiphase batch processes (2014) (3)
- Fault Detection and Identification: Serial Form versus Simultaneous Form (2011) (3)
- Information Fingerprint for Secure Industrial Big Data Analytics (2021) (3)
- Fault variables recognition using improved k-nearest neighbor reconstruction (2017) (3)
- A Spatial-information-based Semi-supervised Soft Sensor for f-CaO Content Prediction in Cement Industry (2020) (2)
- On an Aspect of Implementing Real-Time Optimization: Establishing the Suspending and Activating Conditions Incorporating Process Monitoring (2018) (2)
- Data Guardian: A Data Protection Scheme for Industrial Monitoring Systems (2021) (2)
- Global-local structure analysis for fault detection (2010) (2)
- Dynamic Process Monitoring (2013) (2)
- Enhancing the reliability and accuracy of data-driven dynamic soft sensor based on selective dynamic partial least squares models (2022) (2)
- Dynamic process calibration based on sparse partial least squares (2014) (2)
- Scalable Soft Sensor for Nonlinear Industrial Big Data via Bagging Stochastic Variational Gaussian Processes (2021) (2)
- Improved two-dimensional dynamic batch process monitoring with support vector data description (2011) (2)
- Switching autoregressive dynamic latent variable model for fault detection in multimode processes (2017) (2)
- Nonlinear Variational Bayesian Factor Regression for Inferential Sensor Modeling (2019) (1)
- Improving the Generalization Performance of Data-driven Predictive Model for Dynamic Process Systems (2021) (1)
- Vision‐Based Fan Speed Control System in the Copper Scraps Smelting Process (2015) (1)
- Probabilistic process monitoring with Bayesian regularization (2010) (1)
- Data-Driven Predictive Model Based on Locally Weighted Bayesian Gaussian Regression (2019) (1)
- A Novel Streaming Variational Bayesian Supervised Factor Analysis for Industrial Adaptive Soft Sensor Modeling (2019) (1)
- One-variable attack on the industrial fault classification system and its defense (2022) (1)
- Process structure change detection by eigenvalue-based method (2011) (1)
- Nonlinear Process Monitoring: Part 2 (2013) (0)
- Yarn-Dyed Shirt cut Pieces Defect Detection Using Attention Vector Quantized-Variational Autoencoder (2021) (0)
- Plant-Wide Process Monitoring: Multiblock Method (2013) (0)
- A Novel Scalable Semi-supervised GMM and Its Application for Multimode Process Quality Prediction with Big Data (2018) (0)
- Multi-grain Cascade Recurrent Neural Network for Nonlinear Time-varying Process Soft Sensor Modeling (2019) (0)
- Novel Multimode Process Soft Sensing Methods Based on the Dynamic Mixture Variational Autoencoder Regression Model (2022) (0)
- Security Versus Accuracy: Trade-Off Data Modeling to Safe Fault Classification Systems. (2023) (0)
- Bayesian statistical monitoring of complex semiconductor manufacturing batch processes (2011) (0)
- Nonlinear Inferential Sensor Development Based on GMM–ELM (2019) (0)
- Meta conditional variational auto-encoder for domain generalization (2022) (0)
- Dynamic Processes Modeling and Monitoring based on a Novel Dynamic Latent Variable Model (2019) (0)
- Multimode Process Monitoring: Part 2 (2013) (0)
- Multimode Process Monitoring: Part 1 (2013) (0)
- Back-propagation Based Contribution for nonlinear fault diagnosis (2019) (0)
- Bayesian method for multimode non-Gaussian process monitoring (2009) (0)
- Fault Reconstruction and Identification (2013) (0)
- An Overview of Conventional MSPC Methods (2013) (0)
- Nonlinear fault detection based on locally linear embedding (2013) (0)
- Probabilistic Process Monitoring (2013) (0)
- Attention‐Based Vector Quantization Variational Autoencoder for Colour‐patterned Fabrics Defect Detection (2022) (0)
- Latent and small fault detection and diagnosis for dynamic processes (2008) (0)
- Run-to-run Trajectory Prediction of Uneven-length Batch Processes Using DTW-LSTM (2019) (0)
- Time-Varying Process Monitoring (2013) (0)
- Controlled Variables Adaptation to Improve Process Optimality Using Historical Operating Data (2018) (0)
- Attention-based Stacked Supervised Poisson Autoencoders for Defects Prediction in Casting-rolling process (2022) (0)
- Nonlinear Process Monitoring: Part 1 (2013) (0)
- Multi-layer Monitoring for Parallel Batch Processes with Input Trajectory Adjustment (2018) (0)
- Rapid vision-based system for secondary copper content estimation (2014) (0)
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