Unveiling dynamics changes: Singular spectrum analysis-based method for detecting concept drift in industrial data streams-Reference-Cited by-同舟云学术

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Unveiling dynamics changes: Singular spectrum analysis-based method for detecting concept drift in industrial data streams

Published:2024-06 Issue: Volume:293 Page:111640
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Zhang Yuyan,Liu Zhe^ORCID,Yang Chunjie^ORCID,Huang Xiaoke,Lou Siwei,Zhang Hanwen,Yan Duojin^ORCID

Funder

China Postdoctoral Science Foundation

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference64 articles.

1. Output space transfer based multi-input multi-output Takagi–Sugeno fuzzy modeling for estimation of molten iron quality in blast furnace;Li;Knowl.-Based Syst.,2021

2. Neural networks with upper and lower bound constraints and its application on industrial soft sensing modeling with missing values;Lu;Knowl.-Based Syst.,2022

3. DSTED: A denoising spatial–temporal encoder–decoder framework for multistep prediction of burn-through point in sintering process;Yan;IEEE Trans. Ind. Electron.,2022

4. Fault diagnosis in rotating machines based on transfer learning: literature review;Misbah;Knowl.-Based Syst.,2023

5. A local dynamic broad kernel stationary subspace analysis for monitoring blast furnace ironmaking process;Lou;IEEE Trans. Ind. Inform.,2022

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1. Deep Learning-Based State-of-Health Estimation of Proton-Exchange Membrane Fuel Cells under Dynamic Operation Conditions;Sensors;2024-07-10

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