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

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

Traditional single model based soft sensors may have poor performance on quality prediction for batch processes because of the strong nonlinearity, multiple-phase, and time-varying characteristics. Therefore, a phase partition based ensemble learning framework upon least squares support vector regre...

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Bibliographic Details
Main Authors: Xiaochen Sheng, Weili Xiong
Format: Article
Language:English
Published: AIMS Press 2020-01-01
Series:Mathematical Biosciences and Engineering
Subjects:
nonlinear soft sensor
ensemble learning
least squares support vector regression
phase partition
batch process
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2020100?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/mbe.2020100?viewType=HTML

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