Qingchao Jiang

发表

Just‐in‐time reorganized PCA integrated with SVDD for chemical process monitoring

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2014 .

Weighted kernel principal component analysis based on probability density estimation and moving window and its application in nonlinear chemical process monitoring

Xue-feng Yan, Qingchao Jiang, 2013 .

Fault Detection and Diagnosis in Chemical Processes Using Sensitive Principal Component Analysis

Xue-feng Yan, Qingchao Jiang, Weixiang Zhao, 2013 .

Fault detection in nonlinear chemical processes based on kernel entropy component analysis and angular structure

Xue-feng Yan, Qingchao Jiang, M. Guo, 2013, Korean Journal of Chemical Engineering.

Probabilistic Weighted NPE-SVDD for chemical process monitoring

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2014 .

Joint Probability Density and Double-Weighted Independent Component Analysis for Multimode Non-Gaussian Process Monitoring

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2014 .

Double-Weighted Independent Component Analysis for Non-Gaussian Chemical Process Monitoring

Xuefeng Yan, Chudong Tong, Qingchao Jiang, 2013 .

Application of Neural Network for Nonlinear Predictive Control

Qingchao Jiang, Z. Xu, Bin Zhu, 2012 .

A Multi-SOM with Canonical Variate Analysis for Chemical Process Monitoring and Fault Diagnosis

Yu Song, Xuefeng Yan, Qingchao Jiang, 2014 .

Dynamic Batch Process Monitoring Based on Time-Slice Latent Variable Correlation Analysis

Qingchao Jiang, Le Du, Wenhao Jin, 2022, ACS omega.

Neural network aided approximation and parameter inference of non-Markovian models of gene expression

W. Du, F. Qian, R. Grima, 2021, Nature Communications.

Neural network aided approximation and parameter inference of stochastic models of gene expression

Feng Qian, Zhixing Cao, Qingchao Jiang, 2020, bioRxiv.

Batch process monitoring based on multiple-phase online sorting principal component analysis.

Xuefeng Yan, Qingchao Jiang, Zhaomin Lv, 2016, ISA transactions.

Batch process monitoring based on just-in-time learning and multiple-subspace principal component analysis

Xuefeng Yan, Qingchao Jiang, Zhaomin Lv, 2014 .

Loading-Based Principal Component Selection for PCA Integrated with Support Vector Data Description

Xuefeng Yan, Qingchao Jiang, Bei Wang, 2015 .

Dynamic nonlinear process monitoring based on dynamic correlation variable selection and kernel principal component regression

Xue-feng Yan, Qingchao Jiang, Li Tian, 2022, J. Frankl. Inst..

Distributed-ensemble stacked autoencoder model for non-linear process monitoring

Xuefeng Yan, Li Tian, Qingchao Jiang, 2021, Inf. Sci..

GMM and optimal principal components-based Bayesian method for multimode fault diagnosis

Biao Huang, Xuefeng Yan, Qingchao Jiang, 2016, Comput. Chem. Eng..

Learning Deep Correlated Representations for Nonlinear Process Monitoring

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2019, IEEE Transactions on Industrial Informatics.

Variational Bayesian probabilistic modeling framework for data-driven distributed process monitoring

Qingchao Jiang, Jiashi Jiang, Qingchao Jiang, 2021 .

Data-driven individual–joint learning framework for nonlinear process monitoring

Xuefeng Yan, Jinggao Sun, Qingchao Jiang, 2020 .

Multivariate Statistical Monitoring of Key Operation Units of Batch Processes Based on Time-Slice CCA

Xuefeng Yan, Furong Gao, Qingchao Jiang, 2019, IEEE Transactions on Control Systems Technology.

Multimode Process Monitoring Using Variational Bayesian Inference and Canonical Correlation Analysis

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2019, IEEE Transactions on Automation Science and Engineering.

Quality-Driven Kernel Projection to Latent Structure Model for Nonlinear Process Monitoring

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2019, IEEE Access.

Parallel PCA–KPCA for nonlinear process monitoring

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2018, Control Engineering Practice.

Joint-Individual Monitoring of Parallel-Running Batch Processes Based on MCCA

Yang Wang, Qingchao Jiang, Binbin Li, 2018, IEEE Access.

Optimal Variable Transmission for Distributed Local Fault Detection Incorporating RA and Evolutionary Optimization

Xuefeng Yan, Yang Wang, Qingchao Jiang, 2018, IEEE Access.

Fault information-aided principal component subspace construction for efficient small fault detection for chemical processes

Yang Wang, Qingchao Jiang, Jingqi Fu, 2017, 2017 Chinese Automation Congress (CAC).

Joint-individual monitoring of large-scale chemical processes with multiple interconnected operation units incorporating multiset CCA

Yang Wang, Xuefeng Yan, Qingchao Jiang, 2017 .

FRDPC subspace construction integrated with Bayesian inference for efficient monitoring of dynamic chemical processes

Yang Wang, Qingchao Jiang, Jingqi Fu, 2017, 2017 36th Chinese Control Conference (CCC).

Data-Driven Distributed Local Fault Detection for Large-Scale Processes Based on the GA-Regularized Canonical Correlation Analysis

Yang Wang, Xuefeng Yan, Qingchao Jiang, 2017, IEEE Transactions on Industrial Electronics.

Data-Driven Optimized Distributed Dynamic PCA for Efficient Monitoring of Large-Scale Dynamic Processes

Yang Wang, Qingchao Jiang, Jingqi Fu, 2017, IEEE Access.

Distributed monitoring for large-scale processes based on multivariate statistical analysis and Bayesian method

Biao Huang, Qingchao Jiang, Biao Huang, 2016 .

Performance-driven optimal design of distributed monitoring for large-scale nonlinear processes

Juan Li, Xuefeng Yan, Qingchao Jiang, 2016 .

Independent component analysis model utilizing de-mixing information for improved non-Gaussian process monitoring

Xuefeng Yan, Bei Wang, Qingchao Jiang, 2016, Comput. Ind. Eng..

Nonlinear plant-wide process monitoring using MI-spectral clustering and Bayesian inference-based multiblock KPCA

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2015 .

Fault diagnosis and process monitoring using a statistical pattern framework based on a self-organizing map

Yu Song, Xuefeng Yan, Qingchao Jiang, 2015 .

Plant-wide process monitoring based on mutual information-multiblock principal component analysis.

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2014, ISA transactions.

Improved fault detection in nonlinear chemical processes using WKPCA-SVDD

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2014, Korean Journal of Chemical Engineering.

Fault detection and identification using a Kullback-Leibler divergence based multi-block principal component analysis and bayesian inference

Xuefeng Yan, Bei Wang, Qingchao Jiang, 2014, Korean Journal of Chemical Engineering.

Independent component analysis-based non-Gaussian process monitoring with preselecting optimal components and support vector data description

Xuefeng Yan, Qingchao Jiang, Zhaomin Lv, 2014 .

Fault Detection in Non-Gaussian Processes Based on Mutual Information Weighted Independent Component Analysis

Xuefeng Yan, Qingchao Jiang, Bei Wang, 2014 .

Probabilistic monitoring of chemical processes using adaptively weighted factor analysis and its application

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2014 .

Non-Gaussian chemical process monitoring with adaptively weighted independent component analysis and its applications

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2013 .

Multivariate Statistical Process Monitoring Using Modified Factor Analysis and Its Application

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2012 .

Chemical processes monitoring based on weighted principal component analysis and its application

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2012 .

Multimodal process monitoring based on transition-constrained Gaussian mixture model

Xuefeng Yan, Qingchao Jiang, Shutian Chen, 2020 .

PCA-ICA Integrated with Bayesian Method for Non-Gaussian Fault Diagnosis

Xuefeng Yan, Qingchao Jiang, Juan Li, 2016 .

Imbalanced Classification Based on Minority Clustering Synthetic Minority Oversampling Technique With Wind Turbine Fault Detection Application

Xuefeng Yan, Qingchao Jiang, Huaikuan Yi, 2021, IEEE Transactions on Industrial Informatics.

Review and Perspectives of Data-Driven Distributed Monitoring for Industrial Plant-Wide Processes

Biao Huang, Xuefeng Yan, Qingchao Jiang, 2019, Industrial & Engineering Chemistry Research.

Quality-relevant dynamic process monitoring based on dynamic total slow feature regression model

Haiyong Zheng, Xuefeng Yan, Qingchao Jiang, 2020, Measurement Science and Technology.

Monitoring multi-mode plant-wide processes by using mutual information-based multi-block PCA, joint probability, and Bayesian inference

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2014 .

Considering spatiotemporal evolutionary information in dynamic multi‐objective optimisation

Min Jiang, Qingchao Jiang, Qinqin Fan, 2023, CAAI Transactions on Intelligence Technology.

Data-Driven Two-Dimensional Deep Correlated Representation Learning for Nonlinear Batch Process Monitoring

Furong Gao, Qingchao Jiang, Shifu Yan, 2020, IEEE Transactions on Industrial Informatics.

Data‐driven nonlinear chemical process fault diagnosis based on hierarchical representation learning

Yang Wang, Qingchao Jiang, Qingchao Jiang, 2020 .

Locally Weighted Canonical Correlation Analysis for Nonlinear Process Monitoring

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2018, Industrial & Engineering Chemistry Research.

Efficient Monitoring of Nonlinear Chemical Processes based on Fault-Relevant Kernel Principal Component Subspace Construction and Bayesian Inference

Yang Wang, Qingchao Jiang, Jingqi Fu, 2017 .

Statistical Monitoring of Chemical Processes Based on Sensitive Kernel Principal Components

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2013 .

Data-Driven Batch-End Quality Modeling and Monitoring Based on Optimized Sparse Partial Least Squares

Furong Gao, Xuefeng Yan, Qingchao Jiang, 2020, IEEE Transactions on Industrial Electronics.

A novel multimodal multi-objective optimization algorithm for multi-robot task allocation

Qingchao Jiang, Qinqin Fan, Wentao Huang, 2023, Transactions of the Institute of Measurement and Control.

Performance-Driven Distributed PCA Process Monitoring Based on Fault-Relevant Variable Selection and Bayesian Inference

Biao Huang, Xuefeng Yan, Qingchao Jiang, 2016, IEEE Transactions on Industrial Electronics.

Local–Global Modeling and Distributed Computing Framework for Nonlinear Plant-Wide Process Monitoring With Industrial Big Data

Hui Cheng, Xuefeng Yan, Qingchao Jiang, 2020, IEEE Transactions on Neural Networks and Learning Systems.

Optimized Gaussian-Process-Based Probabilistic Latent Variable Modeling Framework for Distributed Nonlinear Process Monitoring

Xue-feng Yan, Qingchao Jiang, Jiashi Jiang, 2023, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Distributed Robust Process Monitoring Based on Optimized Denoising Autoencoder With Reinforcement Learning

Qingchao Jiang, Shutian Chen, 2022, IEEE Transactions on Instrumentation and Measurement.

Fault Diagnostic Method Based on Deep Learning and Multimodel Feature Fusion for Complex Industrial Processes

Li Tian, Xuefeng Yan, Qingchao Jiang, 2020 .

Deep Discriminative Representation Learning for Nonlinear Process Fault Detection

Xuefeng Yan, Biao Huang, Qingchao Jiang, 2020, IEEE Transactions on Automation Science and Engineering.

Weihua Gui, Chunhua Yang, Xiaofeng Yuan, 2017, 2017 6th International Symposium on Advanced Control of Industrial Processes (AdCONIP).

Neighborhood Stable Correlation Analysis for Robust Monitoring of Multiunit Chemical Processes

Xue-feng Yan, Qingchao Jiang, 2020 .

Multiobjective Two-Dimensional CCA-Based Monitoring for Successive Batch Processes With Industrial Injection Molding Application

Xuefeng Yan, Furong Gao, Qingchao Jiang, 2019, IEEE Transactions on Industrial Electronics.

Bayesian Fault Diagnosis With Asynchronous Measurements and Its Application in Networked Distributed Monitoring

Steven X. Ding, Xuefeng Yan, Qingchao Jiang, 2016, IEEE Transactions on Industrial Electronics.

Data-Driven Soft Sensing for Batch Processes Using Neural Network-Based Deep Quality-Relevant Representation Learning

Zhixing Cao, Qingchao Jiang, Shifu Yan, 2023, IEEE Transactions on Artificial Intelligence.

Dynamic CCA-Based Distributed Monitoring for Multiunit Non-Gaussian Processes

Xuefeng Yan, Qingchao Jiang, Xue-feng Yan, 2018 .

Batch process monitoring based on multiple-phase online sorting principal component analysis.

Xue-feng Yan, Qingchao Jiang, Zhaomin Lv, 2016, ISA transactions.

Neighborhood Variational Bayesian Multivariate Analysis for Distributed Process Monitoring With Missing Data

Biao Huang, Xuefeng Yan, Qingchao Jiang, 2019, IEEE Transactions on Control Systems Technology.

Neural network-based hybrid modeling approach incorporating Bayesian optimization with industrial soft sensor application

Qingchao Jiang, Zhenhua Yu, Zhongyi Zhang, 2024, Knowledge-Based Systems.