Jian Tang
Orcid: 0000-0003-2270-268XAffiliations:
- Beijing University of Technology, College of Electronic and Control Engineering, China
- Northeastern University, Shenyang, China (PhD 2012)
According to our database1,
Jian Tang
authored at least 54 papers
between 2010 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2024
Hybrid Simulator-Based Mechanism and Data-Driven for Multidemand Dioxin Emissions Intelligent Prediction in the MSWI Process.
IEEE Trans. Ind. Electron., October, 2024
IEEE Trans. Neural Networks Learn. Syst., July, 2024
Dynamic System Modeling Using a Multisource Transfer Learning-Based Modular Neural Network for Industrial Application.
IEEE Trans. Ind. Informatics, May, 2024
CO emission predictions in municipal solid waste incineration based on reduced depth features and long short-term memory optimization.
Neural Comput. Appl., April, 2024
Expert Syst. Appl., March, 2024
IEEE Trans. Consumer Electron., February, 2024
Online Measurement of Dioxin Emission in Solid Waste Incineration Using Fuzzy Broad Learning.
IEEE Trans. Ind. Informatics, January, 2024
Multi-reservoir ESN-based prediction strategy for dynamic multi-objective optimization.
Inf. Sci., January, 2024
Eng. Appl. Artif. Intell., 2024
2023
Eng. Appl. Artif. Intell., November, 2023
Time-series prediction using a regularized self-organizing long short-term memory neural network.
Appl. Soft Comput., September, 2023
Virtual sample generation method based on generative adversarial fuzzy neural network.
Neural Comput. Appl., March, 2023
Evolving Deep Delay Echo State Network for Effluent NH<sub>4</sub>-N Prediction in Wastewater Treatment Plants.
IEEE Trans. Instrum. Meas., 2023
Dioxin Emission Concentration Prediction Using the Selective Ensemble Algorithm Based on Bayesian Inference and Binary Tree.
IEEE Trans. Instrum. Meas., 2023
Multiscale Modeling Using GAN and Deep Forest Regression With Application to Dioxin Emission Soft Sensor.
IEEE Trans. Instrum. Meas., 2023
Takagi-Sugeno Fuzzy Regression Trees With Application to Complex Industrial Modeling.
IEEE Trans. Fuzzy Syst., 2023
Carbon Monoxide Emission Prediction Based on Concept Drift Detection Using KPCA for Municipal Solid Waste Incineration Processes.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023
2022
Heterogeneous selective ensemble learning model for mill load parameters forecasting by using multiscale mechanical frequency spectrum.
Soft Comput., December, 2022
NOx Emissions Prediction With a Brain-Inspired Modular Neural Network in Municipal Solid Waste Incineration Processes.
IEEE Trans. Ind. Informatics, 2022
DF classification algorithm for constructing a small sample size of data-oriented DF regression model.
Neural Comput. Appl., 2022
A novel self-organizing TS fuzzy neural network for furnace temperature prediction in MSWI process.
Neural Comput. Appl., 2022
Combustion State Recognition Method in Municipal Solid Waste Incineration Processes Based on Improved Deep Forest.
Proceedings of the Neural Computing for Advanced Applications, 2022
2021
Neural Comput. Appl., 2021
2020
Cooperative Relay Selection for Load Balancing With Mobility in Hierarchical WSNs: A Multi-Armed Bandit Approach.
IEEE Access, 2020
Multisource Latent Feature Selective Ensemble Modeling Approach for Small-Sample High-Dimensional Process Data in Applications.
IEEE Access, 2020
2019
Optimized ensemble modeling based on feature selection using simple sphere criterion for multi-scale mechanical frequency spectrum.
Soft Comput., 2019
Optimising rendezvous-based data collection for target tracking in WSNs with mobile elements.
Int. J. Sens. Networks, 2019
2018
Combinatorial optimization of input features and learning parameters for decorrelated neural network ensemble-based soft measuring model.
Neurocomputing, 2018
Selective Ensemble Modeling Approach based on Variable Importance of Projection With its Application.
Proceedings of the IEEE International Conference on Information and Automation, 2018
2017
Energy-efficient data-gathering rendezvous algorithms with mobile sinks for wireless sensor networks.
Int. J. Sens. Networks, 2017
Modeling collinear data using double-layer GA-based selective ensemble kernel partial least squares algorithm.
Neurocomputing, 2017
Selective Ensemble Random Neural Networks Based on Adaptive Selection Scope of Input Weights and Biases for Building Soft Measuring Model.
Proceedings of the Neural Information Processing - 24th International Conference, 2017
Modeling mill load parameter based on LASSO using multi-scale high dimensional frequency spectra data<sup>1</sup>.
Proceedings of the IEEE International Conference on Information and Automation, 2017
On-Line Intrusion Detection Model Based on Approximate Linear Dependent Condition with Linear Latent Feature Extraction.
Proceedings of the Cloud Computing and Security - Third International Conference, 2017
2016
A Comparative Study That Measures Ball Mill Load Parameters Through Different Single-Scale and Multiscale Frequency Spectra-Based Approaches.
IEEE Trans. Ind. Informatics, 2016
Kernel latent features adaptive extraction and selection method for multi-component non-stationary signal of industrial mechanical device.
Neurocomputing, 2016
Feature selection based on concurrent projection to latent structures for high dimensional spectra data.
Proceedings of the IEEE International Conference on Information and Automation, 2016
Energy-Efficient Data Collection Algorithms Based on Clustering for Mobility-Enabled Wireless Sensor Networks.
Proceedings of the Cloud Computing and Security - Second International Conference, 2016
Supervised Nonlinear Latent Feature Extraction and Regularized Random Weights Neural Network Modeling for Intrusion Detection System.
Proceedings of the Cloud Computing and Security - Second International Conference, 2016
2015
Multi-frequency signal modeling using empirical mode decomposition and PCA with application to mill load estimation.
Neurocomputing, 2015
Modeling high dimensional frequency spectral data based on virtual sample generation technique.
Proceedings of the IEEE International Conference on Information and Automation, 2015
2014
Modeling load parameters of ball mill using frequency spectral features based on Hilbert vibration decomposition.
Proceedings of the IEEE International Conference on Information and Automation, 2014
2013
Modeling Load Parameters of Ball Mill in Grinding Process Based on Selective Ensemble Multisensor Information.
IEEE Trans Autom. Sci. Eng., 2013
2012
Soft Comput., 2012
Neurocomputing, 2012
Soft sensor for parameters of mill load based on multi-spectral segments PLS sub-models and on-line adaptive weighted fusion algorithm.
Neurocomputing, 2012
Modeling Spectral Data Based on Mutual Information and Kernel Extreme Learning Machines.
Proceedings of the Advances in Neural Networks - ISNN 2012, 2012
Proceedings of the Advances in Neural Networks - ISNN 2012, 2012
Feature Selection of Frequency Spectrum for Modeling Difficulty to Measure Process Parameters.
Proceedings of the Advances in Neural Networks - ISNN 2012, 2012
2011
J. Softw., 2011
KPCA based multi-spectral segments feature extraction and GA based Combinatorial optimization for frequency spectrum data modeling.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011
2010
Proceedings of the Third International Workshop on Advanced Computational Intelligence, 2010
Proceedings of the Fifth International Conference on Bio-Inspired Computing: Theories and Applications, 2010