Chunhui Zhao focuses on Algorithm, Data mining, Batch processing, Variable and Statistical model. His study explores the link between Algorithm and topics such as Nonlinear system that cross with problems in Kernel and Kernel. His work carried out in the field of Data mining brings together such families of science as Statistics and Benchmark.
His Mode and Covariance study in the realm of Statistics connects with subjects such as Process analysis and Multi-mode optical fiber. His Statistical model study combines topics from a wide range of disciplines, such as Subspace topology and Cluster analysis. His work deals with themes such as Residual, Projection and Sensitivity, which intersect with Subspace topology.
Data mining, Algorithm, Artificial intelligence, Batch processing and Fault detection and isolation are his primary areas of study. His study in Data mining is interdisciplinary in nature, drawing from both Feature and Benchmark. The concepts of his Algorithm study are interwoven with issues in Subspace topology, Covariance, Regression analysis and Nonlinear system.
His work in the fields of Subspace topology, such as Subspace decomposition, intersects with other areas such as Decomposition. His Artificial intelligence research integrates issues from Machine learning and Pattern recognition. His Principal component analysis research includes elements of Feature and Cointegration.
The scientist’s investigation covers issues in Data mining, Analytics, Feature extraction, Benchmark and Algorithm. His studies in Data mining integrate themes in fields like Convolutional neural network, Root cause and Sequence learning. His study on Analytics also encompasses disciplines like
His Feature extraction study incorporates themes from Statistical classification, Discriminative model and F1 score. He interconnects Energy and Monte Carlo method in the investigation of issues within Algorithm. Chunhui Zhao has researched Elastic net regularization in several fields, including Linear discriminant analysis, Principal component analysis and Residual.
Chunhui Zhao mainly focuses on Data mining, Feature extraction, Benchmark, Data analysis and Task analysis. His Data mining research incorporates themes from Representation and Computation complexity. His Feature extraction study combines topics in areas such as Incremental learning, Convolutional neural network and Root cause.
His Benchmark research is multidisciplinary, incorporating elements of Statistical classification, Random forest, Discriminative model and F1 score. In his study, Algorithm is inextricably linked to Mode, which falls within the broad field of Data analysis. The various areas that Chunhui Zhao examines in his Algorithm study include Mixture model and Range.
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Stage-based soft-transition multiple PCA modeling and on-line monitoring strategy for batch processes
Chunhui Zhao;Fuli Wang;Ningyun Lu;Mingxing Jia.
Journal of Process Control (2007)
A full-condition monitoring method for nonstationary dynamic chemical processes with cointegration and slow feature analysis
Chunhui Zhao;Biao Huang.
Aiche Journal (2018)
Fault-relevant Principal Component Analysis (FPCA) method for multivariate statistical modeling and process monitoring
Chun Hui Zhao;Furong Gao.
Chemometrics and Intelligent Laboratory Systems (2014)
Dynamic Distributed Monitoring Strategy for Large-Scale Nonstationary Processes Subject to Frequently Varying Conditions Under Closed-Loop Control
Chunhui Zhao;He Sun.
IEEE Transactions on Industrial Electronics (2019)
Slow-Feature-Analysis-Based Batch Process Monitoring With Comprehensive Interpretation of Operation Condition Deviation and Dynamic Anomaly
Shumei Zhang;Chunhui Zhao.
IEEE Transactions on Industrial Electronics (2019)
Critical-to-Fault-Degradation Variable Analysis and Direction Extraction for Online Fault Prognostic
Chunhui Zhao;Furong Gao.
IEEE Transactions on Control Systems and Technology (2017)
Statistical analysis and online monitoring for multimode processes with between-mode transitions
Chunhui Zhao;Yuan Yao;Furong Gao;Fuli Wang.
Chemical Engineering Science (2010)
Linearity Evaluation and Variable Subset Partition Based Hierarchical Process Modeling and Monitoring
Wenqing Li;Chunhui Zhao;Furong Gao.
IEEE Transactions on Industrial Electronics (2018)
Broad Convolutional Neural Network Based Industrial Process Fault Diagnosis With Incremental Learning Capability
Wanke Yu;Chunhui Zhao.
IEEE Transactions on Industrial Electronics (2020)
Step-wise sequential phase partition (SSPP) algorithm based statistical modeling and online process monitoring
Chunhui Zhao;Chunhui Zhao;Youxian Sun.
Chemometrics and Intelligent Laboratory Systems (2013)
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