Soft sensor design based on phase partition ensemble of LSSVR models for nonlinear batch processes

DOI10.3934/MBE.2020100zbMath1470.92200OpenAlexW2995319000WikidataQ90792672 ScholiaQ90792672MaRDI QIDQ2045833

Xiaochen Sheng, Weili Xiong

Publication date: 13 August 2021

Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/mbe.2020100

zbMATH Keywords

ensemble learningleast squares support vector regressionbatch processnonlinear soft sensorphase partition

Mathematics Subject Classification ID

Biotechnology (92C75)

Cites Work

• Artificial neural networks in process estimation and control
• Support-vector networks
• Identification of hormone binding proteins based on machine learning methods
• Prediction of crime tendency of high-risk personnel using C5.0 decision tree empowered by particle swarm optimization
• A note on model selection using information criteria for general linear models estimated using REML

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