Classification of the Degradation of Soft Sensor Models and Discussion on Adaptive Models-Reference-Cited by-同舟云学术

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Classification of the Degradation of Soft Sensor Models and Discussion on Adaptive Models

Published:2013-01-14 Issue:7 Volume:59 Page:2339-2347
ISSN:0001-1541
Container-title:AIChE Journal
language:en
Short-container-title:AIChE J.

Author:

Kaneko Hiromasa¹,Funatsu Kimito¹

Affiliation:

1. Dept. of Chemical System Engineering; The University of Tokyo; Hongo 7-3-1, Bunkyo-ku; Tokyo; 113-8656; Japan

Publisher

Wiley

Subject

General Chemical Engineering,Environmental Engineering,Biotechnology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/aic.14006/fullpdf

Reference12 articles.

1. Data-based process monitoring, process control, and quality improvement: recent developments and applications in steel industry;Kano;Comput Chem Eng.,2008

2. Data-driven soft sensors in the process industry;Kadlec;Comput Chem Eng.,2009

3. Development of a new soft sensor method using independent component analysis and partial least squares;Kaneko;AIChE J.,2009

4. Applicability domains and accuracy of prediction of soft sensor models;Kaneko;AIChE J.,2011

5. Local learning-based adaptive soft sensor for catalyst activation prediction;Kadlec;AIChE J.,2010

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2. Modeling an Adaptive Hybrid Soft Sensor with Co-training Learning toward Applications in Wastewater Treatment;Industrial & Engineering Chemistry Research;2023-10-09

3. Efficient JITL framework for nonlinear industrial chemical engineering soft sensing based on adaptive multi-branch variable scale integrated convolutional neural networks;Advanced Engineering Informatics;2023-10

4. Just-in-time based soft sensors for process industries: A status report and recommendations;Journal of Process Control;2023-08

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