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Application of fuzzy partial least squares (FPLS) modeling nonlinear biological processes

Yoo, CK; Bang, YH; Lee, IB; Vanrolleghem, PA and Rosén, Christian LU (2004) In Korean Journal of Chemical Engineering 21(6). p.1087-1097
Abstract
We applied a nonlinear fuzzy partial least squares (FPLS) algorithm for modeling a biological wastewater treatment plant. FPLS embeds the Takagi-Sugeno-Kang (TSK) fuzzy model into the regression framework of the partial least squares (PLS) method, in which FPLS utilizes a TSK fuzzy model for nonlinear characteristics of the PLS inner regression. Using this approach, the interpretability of the TSK fuzzy model overcomes some of the handicaps of previous nonlinear PLS (NLPLS) algorithms. As a result, the FPLS model gives a more favorable modeling environment in which the knowledge of experts can be easily applied. Results from applications show that FPLS has the ability to model the nonlinear process and multiple operating conditions and is... (More)
We applied a nonlinear fuzzy partial least squares (FPLS) algorithm for modeling a biological wastewater treatment plant. FPLS embeds the Takagi-Sugeno-Kang (TSK) fuzzy model into the regression framework of the partial least squares (PLS) method, in which FPLS utilizes a TSK fuzzy model for nonlinear characteristics of the PLS inner regression. Using this approach, the interpretability of the TSK fuzzy model overcomes some of the handicaps of previous nonlinear PLS (NLPLS) algorithms. As a result, the FPLS model gives a more favorable modeling environment in which the knowledge of experts can be easily applied. Results from applications show that FPLS has the ability to model the nonlinear process and multiple operating conditions and is able to identify various operating regions in a simulation benchmark of biological process as well as in a full-scale wastewater treatment process. The result shows that it has the ability to model the nonlinear process and handle multiple operating conditions and is able to predict the key components of nonlinear biological processes. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
partial least squares (PLS), nonlinear PLS (NLPLS), nonlinear modeling, fuzzy partial least squares (FPLS), multivariate statistical analysis, wastewater treatment process (WWTP)
in
Korean Journal of Chemical Engineering
volume
21
issue
6
pages
1087 - 1097
publisher
Springer
external identifiers
  • wos:000225818000001
  • scopus:13444262016
ISSN
0256-1115
DOI
10.1007/BF02719479
language
English
LU publication?
yes
id
e001d97b-e419-4788-b386-4e98cc3d5517 (old id 258347)
date added to LUP
2007-11-07 08:41:50
date last changed
2017-09-03 04:42:31
@article{e001d97b-e419-4788-b386-4e98cc3d5517,
  abstract     = {We applied a nonlinear fuzzy partial least squares (FPLS) algorithm for modeling a biological wastewater treatment plant. FPLS embeds the Takagi-Sugeno-Kang (TSK) fuzzy model into the regression framework of the partial least squares (PLS) method, in which FPLS utilizes a TSK fuzzy model for nonlinear characteristics of the PLS inner regression. Using this approach, the interpretability of the TSK fuzzy model overcomes some of the handicaps of previous nonlinear PLS (NLPLS) algorithms. As a result, the FPLS model gives a more favorable modeling environment in which the knowledge of experts can be easily applied. Results from applications show that FPLS has the ability to model the nonlinear process and multiple operating conditions and is able to identify various operating regions in a simulation benchmark of biological process as well as in a full-scale wastewater treatment process. The result shows that it has the ability to model the nonlinear process and handle multiple operating conditions and is able to predict the key components of nonlinear biological processes.},
  author       = {Yoo, CK and Bang, YH and Lee, IB and Vanrolleghem, PA and Rosén, Christian},
  issn         = {0256-1115},
  keyword      = {partial least squares (PLS),nonlinear PLS (NLPLS),nonlinear modeling,fuzzy partial least squares (FPLS),multivariate statistical analysis,wastewater treatment process (WWTP)},
  language     = {eng},
  number       = {6},
  pages        = {1087--1097},
  publisher    = {Springer},
  series       = {Korean Journal of Chemical Engineering},
  title        = {Application of fuzzy partial least squares (FPLS) modeling nonlinear biological processes},
  url          = {http://dx.doi.org/10.1007/BF02719479},
  volume       = {21},
  year         = {2004},
}