Adaptive non-linear soft sensor for quality monitoring in refineries using Just-in-Time Learning—Generalized regression neural network approach-Reference-Cited by-同舟云学术

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Adaptive non-linear soft sensor for quality monitoring in refineries using Just-in-Time Learning—Generalized regression neural network approach

Published:2022-04 Issue: Volume:119 Page:108546
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

S. Venkata Vijayan,Mohanta Hare K.,Pani Ajaya Kumar^ORCID

Publisher

Elsevier BV

Subject

Software

Reference55 articles.

1. Moving average PLS soft sensor for online product quality estimation in an industrial batch polymerization process;Facco;J. Process Control,2009

2. A new data-based methodology for nonlinear process modeling;Cheng;Chem. Eng. Sci.,2004

3. Review of adaptation mechanisms for data-driven soft sensors;Kadlec;Comput. Chem. Eng.,2011

4. Moving window and just-in-time soft sensor model based on time differences considering a small number of measurements;Kaneko;Ind. Eng. Chem. Res.,2015

5. Integrating adaptive moving window and just-in-time learning paradigms for soft-sensor design;Urhan;Neurocomputing,2020

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