What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Machine learning
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.
His most cited work include:
- Stage-based soft-transition multiple PCA modeling and on-line monitoring strategy for batch processes (145 citations)
- Fault-relevant Principal Component Analysis (FPCA) method for multivariate statistical modeling and process monitoring (104 citations)
- A full‐condition monitoring method for nonstationary dynamic chemical processes with cointegration and slow feature analysis (79 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Data mining (35.00%)
- Algorithm (27.27%)
- Artificial intelligence (20.91%)
What were the highlights of his more recent work (between 2019-2021)?
- Data mining (35.00%)
- Analytics (7.27%)
- Feature extraction (5.91%)
In recent papers he was focusing on the following fields of study:
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
- Feature that intertwine with fields like Identification, Control and Latent variable,
- Representation which intersects with area such as Computation complexity.
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.
Between 2019 and 2021, his most popular works were:
- Robust Monitoring and Fault Isolation of Nonlinear Industrial Processes Using Denoising Autoencoder and Elastic Net (29 citations)
- Broad Convolutional Neural Network Based Industrial Process Fault Diagnosis With Incremental Learning Capability (27 citations)
- Enhanced Random Forest With Concurrent Analysis of Static and Dynamic Nodes for Industrial Fault Classification (27 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Machine learning
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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