Adaptive Multioutput Gradient RBF Tracker for Nonlinear and Nonstationary Regression-Reference-Cited by-同舟云学术

Adaptive Multioutput Gradient RBF Tracker for Nonlinear and Nonstationary Regression

Published:2023-12 Issue:12 Volume:53 Page:7906-7919
ISSN:2168-2267
Container-title:IEEE Transactions on Cybernetics
language:
Short-container-title:IEEE Trans. Cybern.

Author:

Liu Tong¹^ORCID,Chen Sheng²^ORCID,Li Kang³^ORCID,Gan Shaojun⁴^ORCID,Harris Chris J.²^ORCID

Affiliation:

1. Department of Chemical Engineering, Imperial College London, London, U.K

2. School of Electronics and Computer Science, University of Southampton, Southampton, U.K

3. School of Electronic and Electrical Engineering, University of Leeds, Leeds, U.K

4. Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Information Systems,Control and Systems Engineering,Software

Link

http://xplorestaging.ieee.org/ielx7/6221036/10334428/10035301.pdf?arnumber=10035301

Reference56 articles.

1. Selective ensemble of multiple local model learning for nonlinear and nonstationary systems

2. Adaptive Soft Sensor Development for Multi-Output Industrial Processes Based on Selective Ensemble Learning

3. Development of RVM-Based Multiple-Output Soft Sensors With Serial and Parallel Stacking Strategies

4. Multi-Output Selective Ensemble Identification of Nonlinear and Nonstationary Industrial Processes

5. Growing and Pruning Selective Ensemble Regression for Nonlinear and Nonstationary Systems

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