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Incipient fault detection for nonlinear processes based on dynamic multi-block probability related kernel principal component analysis

ISA transactions, 2020-10, Vol.105, p.210-220

2020

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Nonlinear Process Fault Diagnosis Based on Serial Principal Component Analysis

IEEE transaction on neural networks and learning systems, 2018-03, Vol.29 (3), p.560-572

2018

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Two-Step Localized Kernel Principal Component Analysis Based Incipient Fault Diagnosis for Nonlinear Industrial Processes

Industrial & engineering chemistry research, 2020-04, Vol.59 (13), p.5956-5968

2020

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Nonlinear Chemical Process Fault Diagnosis Using Ensemble Deep Support Vector Data Description

Sensors (Basel, Switzerland), 2020-08, Vol.20 (16), p.4599

2020

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Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs

European radiology, 2020-02, Vol.30 (2), p.823-832

2020

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Modified kernel principal component analysis using double-weighted local outlier factor and its application to nonlinear process monitoring

ISA transactions, 2018-01, Vol.72, p.218-228

2018

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State-of-Health Prediction For Lithium-Ion Batteries With Multiple Gaussian Process Regression Model

IEEE access, 2019, Vol.7, p.150383-150394

2019

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Nonlinear process fault pattern recognition using statistics kernel PCA similarity factor

Neurocomputing (Amsterdam), 2013-12, Vol.121, p.298-308

2013

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Analysis of Discontinuity Detectors and Hybrid WCNS Schemes Based on Waveform Recognition

Communications in computational physics, 2023-08, Vol.34 (2), p.418-455

2023

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Boosting‐based cascaded convolutional neural networks for the segmentation of CT organs‐at‐risk in nasopharyngeal carcinoma

Medical Physics, 2019-12, Vol.46 (12), p.5602-5611

2019

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New optimized flux difference schemes for improving high-order weighted compact nonlinear scheme with applications

Applied mathematics and mechanics, 2021-03, Vol.42 (3), p.405-424

English ed., 2021

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A class of hybrid DG/FV methods for conservation laws I: Basic formulation and one-dimensional systems

Journal of computational physics, 2012-02, Vol.231 (4), p.1081-1103

2012

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Geometric conservation law and applications to high-order finite difference schemes with stationary grids

Journal of computational physics, 2011-02, Vol.230 (4), p.1100-1115

2011

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WCNS schemes and some recent developments

Advances in aerodynamics, 2024-01, Vol.6 (1), p.2-17, Article 2

2024

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Sparse Kernel Locality Preserving Projection and Its Application in Nonlinear Process Fault Detection

Chinese journal of chemical engineering, 2013-02, Vol.21 (2), p.163-170

2013

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Assessment of alternative scale-providing variables in a Reynolds-stress model using high-order methods

Acta mechanica Sinica, 2022-12, Vol.38 (12), Article 322151

English ed., 2022

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A Scale-Invariant Fifth Order WCNS Scheme for Hyperbolic Conservation Laws

Advances in applied mathematics and mechanics, 2023-10, Vol.15 (5), p.1256-1289

2023

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A class of hybrid DG/FV methods for conservation laws II: Two-dimensional cases

Journal of computational physics, 2012-02, Vol.231 (4), p.1104-1120

2012

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Multiderivative Combined Dissipative Compact Scheme Satisfying Geometric Conservation Law III: Characteristic-Wise Hybrid Method

Advances in applied mathematics and mechanics, 2022, Vol.14 (2), p.415-441

2022

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Batch Process Monitoring Based on Multiway Global Preserving Kernel Slow Feature Analysis

IEEE access, 2017, Vol.5, p.2696-2710

2017

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A Lifting Method for Krause’s Consensus Model

Communications in Mathematical Research, 2022-01, Vol.38 (1), p.52-61

2022

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Anomaly detection using improved deep SVDD model with data structure preservation

Pattern recognition letters, 2021-08, Vol.148, p.1-6

2021

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Deep Convolutional Feature-Based Probabilistic SVDD Method for Monitoring Incipient Faults of Batch Process

Energies (Basel), 2021-06, Vol.14 (11), p.3334

2021

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An implicit parallel UGKS solver for flows covering various regimes

Advances in aerodynamics, 2019-03, Vol.1 (1), p.8-24, Article 8

2019

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High-order discretization of the Reynolds stress model with an εβ-adaptive algorith

Acta mechanica Sinica, 2022-06, Vol.38 (6), Article 321357

English ed., 2022

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Incipient fault detection for nonlinear processes based on dynamic multi-block probability related kernel principal component analysis

Nonlinear Process Fault Diagnosis Based on Serial Principal Component Analysis

Two-Step Localized Kernel Principal Component Analysis Based Incipient Fault Diagnosis for Nonlinear Industrial Processes

Nonlinear Chemical Process Fault Diagnosis Using Ensemble Deep Support Vector Data Description

Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs

Modified kernel principal component analysis using double-weighted local outlier factor and its application to nonlinear process monitoring

State-of-Health Prediction For Lithium-Ion Batteries With Multiple Gaussian Process Regression Model

Nonlinear process fault pattern recognition using statistics kernel PCA similarity factor

Analysis of Discontinuity Detectors and Hybrid WCNS Schemes Based on Waveform Recognition

Boosting‐based cascaded convolutional neural networks for the segmentation of CT organs‐at‐risk in nasopharyngeal carcinoma

New optimized flux difference schemes for improving high-order weighted compact nonlinear scheme with applications

A class of hybrid DG/FV methods for conservation laws I: Basic formulation and one-dimensional systems

Geometric conservation law and applications to high-order finite difference schemes with stationary grids

WCNS schemes and some recent developments

Sparse Kernel Locality Preserving Projection and Its Application in Nonlinear Process Fault Detection

Assessment of alternative scale-providing variables in a Reynolds-stress model using high-order methods

A Scale-Invariant Fifth Order WCNS Scheme for Hyperbolic Conservation Laws

A class of hybrid DG/FV methods for conservation laws II: Two-dimensional cases

Multiderivative Combined Dissipative Compact Scheme Satisfying Geometric Conservation Law III: Characteristic-Wise Hybrid Method

Batch Process Monitoring Based on Multiway Global Preserving Kernel Slow Feature Analysis

A Lifting Method for Krause’s Consensus Model

Anomaly detection using improved deep SVDD model with data structure preservation

Deep Convolutional Feature-Based Probabilistic SVDD Method for Monitoring Incipient Faults of Batch Process

An implicit parallel UGKS solver for flows covering various regimes

High-order discretization of the Reynolds stress model with an εβ-adaptive algorith

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