A variable selection and structure optimization algorithm for online sequence extreme learning machine-Reference-Cited by-同舟云学术

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A variable selection and structure optimization algorithm for online sequence extreme learning machine

Published:2022-05-04 Issue: Volume: Page:
ISSN:
Container-title:2022 13th Asian Control Conference (ASCC)
language:
Short-container-title:

Author:

Zhao Yadong¹,Sun Tao¹,Zhao Jianjun²,Sun Kai¹

Affiliation:

1. Qilu University of Technology(Shandong Acadamy of Sciences),School of Information and Automation,Jinan,China

2. Beijing Key Laboratory of Process Automation in Mining & Metallurgy,State Key Laboratory of Process Automation in Mining & Metallurgy,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9828005/9828007/09828245.pdf?arnumber=9828245

Reference20 articles.

1. A Novel Input Variable Selection and Structure Optimization Algorithm for Multilayer Perceptron-Based Soft Sensors

2. Adaptive control of nonlinear system using online error minimum neural networks

3. OP-ELM: Optimally Pruned Extreme Learning Machine

4. An improved OS-ELM based real-time prognostic method towards singularity perturbation phenomenon. Measurement;yan,2021

5. An efficient online sequential extreme learning machine model based on feature selection and parameter optimization using cuckoo search algorithm for multi-step wind speed forecasting

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