Transforming data into knowledge for improved wastewater treatment operation : A critical review of techniques
(2018) In Environmental Modelling and Software 106. p.89-103- Abstract
The aim of this paper is to describe the state-of-the art computer-based techniques for data analysis to improve operation of wastewater treatment plants. A comprehensive review of peer-reviewed papers shows that European researchers have led academic computer-based method development during the last two decades. The most cited techniques are artificial neural networks, principal component analysis, fuzzy logic, clustering, independent component analysis and partial least squares regression. Even though there has been progress on techniques related to the development of environmental decision support systems, knowledge discovery and management, the research sector is still far from delivering systems that smoothly integrate several... (More)
The aim of this paper is to describe the state-of-the art computer-based techniques for data analysis to improve operation of wastewater treatment plants. A comprehensive review of peer-reviewed papers shows that European researchers have led academic computer-based method development during the last two decades. The most cited techniques are artificial neural networks, principal component analysis, fuzzy logic, clustering, independent component analysis and partial least squares regression. Even though there has been progress on techniques related to the development of environmental decision support systems, knowledge discovery and management, the research sector is still far from delivering systems that smoothly integrate several types of knowledge and different methods of reasoning. Several limitations that currently prevent the application of computer-based techniques in practice are highlighted.
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- author
- Corominas, Ll ; Garrido-Baserba, M. ; Villez, K. ; Olsson, G. LU ; Cortés, U. and Poch, M. LU
- organization
- publishing date
- 2018
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Data mining, Data processing, Data quality, Knowledge, WWTP
- in
- Environmental Modelling and Software
- volume
- 106
- pages
- 89 - 103
- publisher
- Elsevier
- external identifiers
-
- scopus:85044678780
- ISSN
- 1364-8152
- DOI
- 10.1016/j.envsoft.2017.11.023
- language
- English
- LU publication?
- yes
- id
- c8e74c89-0912-4ff8-b6a1-727da6910f2d
- date added to LUP
- 2018-04-12 15:04:48
- date last changed
- 2022-04-25 06:42:50
@article{c8e74c89-0912-4ff8-b6a1-727da6910f2d,
abstract = {{<p>The aim of this paper is to describe the state-of-the art computer-based techniques for data analysis to improve operation of wastewater treatment plants. A comprehensive review of peer-reviewed papers shows that European researchers have led academic computer-based method development during the last two decades. The most cited techniques are artificial neural networks, principal component analysis, fuzzy logic, clustering, independent component analysis and partial least squares regression. Even though there has been progress on techniques related to the development of environmental decision support systems, knowledge discovery and management, the research sector is still far from delivering systems that smoothly integrate several types of knowledge and different methods of reasoning. Several limitations that currently prevent the application of computer-based techniques in practice are highlighted.</p>}},
author = {{Corominas, Ll and Garrido-Baserba, M. and Villez, K. and Olsson, G. and Cortés, U. and Poch, M.}},
issn = {{1364-8152}},
keywords = {{Data mining; Data processing; Data quality; Knowledge; WWTP}},
language = {{eng}},
pages = {{89--103}},
publisher = {{Elsevier}},
series = {{Environmental Modelling and Software}},
title = {{Transforming data into knowledge for improved wastewater treatment operation : A critical review of techniques}},
url = {{http://dx.doi.org/10.1016/j.envsoft.2017.11.023}},
doi = {{10.1016/j.envsoft.2017.11.023}},
volume = {{106}},
year = {{2018}},
}