Yalin Wang
Orcid: 0000-0002-1876-7707Affiliations:
- Central South University, School of Automation, Changsha, China
- University of Washington, Seattle, WA, USA (former)
- Central South University, Department of Control Science and Engineering, Changsha, China (PhD 2001)
According to our database1,
Yalin Wang
authored at least 91 papers
between 2004 and 2025.
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Bibliography
2025
Interpretable Switching Deep Markov Model for Industrial Process Monitoring via Cloud-Edge Collaborative Framework.
IEEE Trans. Instrum. Meas., 2025
2024
Scope-Free Global Multi-Condition-Aware Industrial Missing Data Imputation Framework via Diffusion Transformer.
IEEE Trans. Knowl. Data Eng., November, 2024
Adaptive Attention-Driven Manifold Regularization for Deep Learning Networks: Industrial Predictive Modeling Applications and Beyond.
IEEE Trans. Ind. Electron., October, 2024
Improved Adaptive Large Neighborhood Search Algorithm Based on the Two-Stage Framework for Scheduling Multiple Super-Agile Satellites.
IEEE Trans. Aerosp. Electron. Syst., October, 2024
A Deep Residual PLS for Data-Driven Quality Prediction Modeling in Industrial Process.
IEEE CAA J. Autom. Sinica, August, 2024
Maximizing Anomaly Detection Performance Using Latent Variable Models in Industrial Systems.
IEEE Trans Autom. Sci. Eng., July, 2024
IEEE Trans. Neural Networks Learn. Syst., May, 2024
Operating Condition Recognition of Industrial Flotation Processes Using Visual and Acoustic Bimodal Autoencoder With Manifold Learning.
IEEE Trans. Ind. Informatics, May, 2024
Quality Prediction Modeling for Industrial Processes Using Multiscale Attention-Based Convolutional Neural Network.
IEEE Trans. Cybern., May, 2024
Attention-Based Interval Aided Networks for Data Modeling of Heterogeneous Sampling Sequences With Missing Values in Process Industry.
IEEE Trans. Ind. Informatics, April, 2024
Blackout Missing Data Recovery in Industrial Time Series Based on Masked-Former Hierarchical Imputation Framework.
IEEE Trans Autom. Sci. Eng., April, 2024
Multiscale Feature Fusion and Semi-Supervised Temporal-Spatial Learning for Performance Monitoring in the Flotation Industrial Process.
IEEE Trans. Cybern., February, 2024
Appl. Intell., February, 2024
Interpretable Prediction Modeling for Froth Flotation via Stacked Graph Convolutional Network.
IEEE Trans. Artif. Intell., January, 2024
Multimodal Data-Driven Reinforcement Learning for Operational Decision-Making in Industrial Processes.
IEEE CAA J. Autom. Sinica, January, 2024
Variable Correlation Analysis-Based Convolutional Neural Network for Far Topological Feature Extraction and Industrial Predictive Modeling.
IEEE Trans. Instrum. Meas., 2024
Missing-Data Imputation With Position-Encoding Denoising Autoencoders for Industrial Processes.
IEEE Trans. Instrum. Meas., 2024
Multirate-Former: An Efficient Transformer-Based Hierarchical Network for Multistep Prediction of Multirate Industrial Processes.
IEEE Trans. Instrum. Meas., 2024
Exploring interpretable evolutionary optimization via significance of each constraint and population diversity.
Swarm Evol. Comput., 2024
Unveiling the potential of progressive training diffusion model for defect image generation and recognition in industrial processes.
Neurocomputing, 2024
Residual-aware deep attention graph convolutional network via unveiling data latent interactions for product quality prediction in industrial processes.
Expert Syst. Appl., 2024
Anomaly detection using large-scale multimode industrial data: An integration method of nonstationary kernel and autoencoder.
Eng. Appl. Artif. Intell., 2024
A task-oriented deep learning framework based on target-related transformer network for industrial quality prediction applications.
Eng. Appl. Artif. Intell., 2024
Generation of Uncorrelated Residual Variables for Chemical Process Fault Diagnosis via Transfer Learning-based Input-Output Decoupled Network.
CoRR, 2024
A novel network for semantic segmentation of landslide areas in remote sensing images with multi-branch and multi-scale fusion.
Appl. Soft Comput., 2024
Genetic Algorithm Driven by Translational Mutation Operator for the Scheduling Optimization in the Steelmaking-Continuous Casting Production.
Proceedings of the Intelligent Information Processing XII, 2024
2023
Neuron-Compressed Deep Neural Network and Its Application in Industrial Anomaly Detection.
IEEE Trans. Ind. Informatics, July, 2023
Semi-supervised deep embedded clustering with pairwise constraints and subset allocation.
Neural Networks, July, 2023
Inf. Sci., June, 2023
Revolutionizing Flotation Process Working Condition Identification Based on Froth Audio.
IEEE Trans. Instrum. Meas., 2023
Data Mode Related Interpretable Transformer Network for Predictive Modeling and Key Sample Analysis in Industrial Processes.
IEEE Trans. Ind. Informatics, 2023
Imputation of Missing Values in Time Series Using an Adaptive-Learned Median-Filled Deep Autoencoder.
IEEE Trans. Cybern., 2023
No-Delay Multimodal Process Monitoring Using Kullback-Leibler Divergence-Based Statistics in Probabilistic Mixture Models.
IEEE Trans Autom. Sci. Eng., 2023
Semi-supervised LSTM with historical feature fusion attention for temporal sequence dynamic modeling in industrial processes.
Eng. Appl. Artif. Intell., 2023
Promoting Decision-Making in Industrial Flotation Process by Collaborating Multiple Flotation Cells.
Proceedings of the 49th Annual Conference of the IEEE Industrial Electronics Society, 2023
Reinforcement Learning-based Operational Decision-Making in the Process Industry Using Multi-View Data.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023
Communication and Self-Learning Strategies Incorporated State Transition Algorithm for Optimization of Complex Systems.
Proceedings of the CAA Symposium on Fault Detection, 2023
2022
Deep Neural Network-Embedded Stochastic Nonlinear State-Space Models and Their Applications to Process Monitoring.
IEEE Trans. Neural Networks Learn. Syst., 2022
Layer-Wise Residual-Guided Feature Learning With Deep Learning Networks for Industrial Quality Prediction.
IEEE Trans. Instrum. Meas., 2022
Learning Deep Multimanifold Structure Feature Representation for Quality Prediction With an Industrial Application.
IEEE Trans. Ind. Informatics, 2022
A reduced nonstationary discrete convolution kernel for multimode process monitoring.
Int. J. Mach. Learn. Cybern., 2022
New mode cold start monitoring in industrial processes: A solution of spatial-temporal feature transfer.
Knowl. Based Syst., 2022
Online reconstruction and diagnosibility analysis of multiplicative fault models for process-related faults.
J. Frankl. Inst., 2022
Dynamic historical information incorporated attention deep learning model for industrial soft sensor modeling.
Adv. Eng. Informatics, 2022
A multi-source transfer learning method for new mode monitoring in industrial processes.
Proceedings of the 8th International Conference on Control, 2022
2021
A Layer-Wise Data Augmentation Strategy for Deep Learning Networks and Its Soft Sensor Application in an Industrial Hydrocracking Process.
IEEE Trans. Neural Networks Learn. Syst., 2021
IEEE Trans. Instrum. Meas., 2021
Deep Learning for Data Modeling of Multirate Quality Variables in Industrial Processes.
IEEE Trans. Instrum. Meas., 2021
Deep Nonlinear Dynamic Feature Extraction for Quality Prediction Based on Spatiotemporal Neighborhood Preserving SAE.
IEEE Trans. Instrum. Meas., 2021
An Efficient Computational Cost Reduction Strategy for the Population-Based Intelligent Optimization of Nonlinear Dynamical Systems.
IEEE Trans. Ind. Informatics, 2021
Deep Learning With Spatiotemporal Attention-Based LSTM for Industrial Soft Sensor Model Development.
IEEE Trans. Ind. Electron., 2021
Supervised and semi-supervised probabilistic learning with deep neural networks for concurrent process-quality monitoring.
Neural Networks, 2021
A classification-driven neuron-grouped SAE for feature representation and its application to fault classification in chemical processes.
Knowl. Based Syst., 2021
Deep learning with neighborhood preserving embedding regularization and its application for soft sensor in an industrial hydrocracking process.
Inf. Sci., 2021
A Gaussian mixture model based virtual sample generation approach for small datasets in industrial processes.
Inf. Sci., 2021
Common and specific deep feature representation for multimode process monitoring using a novel variable-wise weighted parallel network.
Eng. Appl. Artif. Intell., 2021
Deep learning with nonlocal and local structure preserving stacked autoencoder for soft sensor in industrial processes.
Eng. Appl. Artif. Intell., 2021
A novel adaptive generic model control strategy for internal thermally coupled air separation columns with multivariable recursive estimation.
Comput. Chem. Eng., 2021
An online operating performance evaluation approach using probabilistic fuzzy theory for chemical processes with uncertainties.
Comput. Chem. Eng., 2021
A fault reconstruction strategy for fault diagnosis of state-related multiplicative faults.
Proceedings of the CAA Symposium on Fault Detection, 2021
Quality-Sensitive Feature Extraction for End Product Quality Prediction in Injection Molding Processes.
Proceedings of the Big Data - 9th CCF Conference, 2021
2020
A Deep Supervised Learning Framework for Data-Driven Soft Sensor Modeling of Industrial Processes.
IEEE Trans. Neural Networks Learn. Syst., 2020
IEEE Trans. Instrum. Meas., 2020
Hierarchical Quality-Relevant Feature Representation for Soft Sensor Modeling: A Novel Deep Learning Strategy.
IEEE Trans. Ind. Informatics, 2020
Nonlinear Dynamic Soft Sensor Modeling With Supervised Long Short-Term Memory Network.
IEEE Trans. Ind. Informatics, 2020
Stacked isomorphic autoencoder based soft analyzer and its application to sulfur recovery unit.
Inf. Sci., 2020
Deep quality-related feature extraction for soft sensing modeling: A deep learning approach with hybrid VW-SAE.
Neurocomputing, 2020
LDA-based deep transfer learning for fault diagnosis in industrial chemical processes.
Comput. Chem. Eng., 2020
2019
Distributed consensus of high-order continuous-time multi-agent systems with nonconvex input constraints, switching topologies, and delays.
Neurocomputing, 2019
A Feedforward Decoupling Dynamic Matrix Control of Heavy Oil Separated Process with Smith Predictive Compensation Principle.
Proceedings of the 12th Asian Control Conference, 2019
Fuzzy C-means Cluster Based on Local Weighted Principal Component Regression for Soft Sensor of an Industrial Hydrocracking process.
Proceedings of the 12th Asian Control Conference, 2019
Parameter Optimization of Hydrocracker using Multi-block Kriging Metamodeling within Discontinuous Operating Space.
Proceedings of the 12th Asian Control Conference, 2019
A correction method for the proportion of key components in basic HYSYS library based on an improved squirrel search algorithm.
Proceedings of the 12th Asian Control Conference, 2019
2018
Deep Learning-Based Feature Representation and Its Application for Soft Sensor Modeling With Variable-Wise Weighted SAE.
IEEE Trans. Ind. Informatics, 2018
Weighted Linear Dynamic System for Feature Representation and Soft Sensor Application in Nonlinear Dynamic Industrial Processes.
IEEE Trans. Ind. Electron., 2018
Distributed defect recognition on steel surfaces using an improved random forest algorithm with optimal multi-feature-set fusion.
Multim. Tools Appl., 2018
Probabilistic Nonlinear Soft Sensor Modeling Based on Generative Topographic Mapping Regression.
IEEE Access, 2018
Sulfur Flotation Performance Recognition Based on Hierarchical Classification of Local Dynamic and Static Froth Features.
IEEE Access, 2018
A Novel Sliding Window PCA-IPF Based Steady-State Detection Framework and Its Industrial Application.
IEEE Access, 2018
Nonlinear VW-SAE Based Deep Learning for Quality-Related Feature Learning and Soft Sensor Modeling.
Proceedings of the IECON 2018, 2018
2017
Soft Sensor Modeling of Nonlinear Industrial Processes Based on Weighted Probabilistic Projection Regression.
IEEE Trans. Instrum. Meas., 2017
Semisupervised JITL Framework for Nonlinear Industrial Soft Sensing Based on Locally Semisupervised Weighted PCR.
IEEE Trans. Ind. Informatics, 2017
Neurocomputing, 2017
Power Consumption Prediction for Dynamic Adjustment in Hydrocracking Process Based on State Transition Algorithm and Support Vector Machine.
Proceedings of the Neural Information Processing - 24th International Conference, 2017
2016
Proceedings of the Neural Information Processing - 23rd International Conference, 2016
2013
A Hybrid Multiobjective Differential Evolution Algorithm and Its Application to the Optimization of Grinding and Classification.
J. Appl. Math., 2013
2011
Appl. Math. Lett., 2011
2009
A two-stage intelligent optimization system for the raw slurry preparing process of alumina sintering production.
Eng. Appl. Artif. Intell., 2009
Modeling and optimal-setting control of blending process in a metallurgical industry.
Comput. Chem. Eng., 2009
2006
Proceedings of the First International Conference on Innovative Computing, Information and Control (ICICIC 2006), 30 August, 2006
2004
Multi-step optimal control of complex process: a genetic programming strategy and its application.
Eng. Appl. Artif. Intell., 2004