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Application of artificial neural networks in wastewater treatment.

Authors :
El-Din, Ahmed Gamal
Smith, Daniel W.
El-Din, Mohamed Gamal
Source :
Journal of Environmental Engineering & Science. Apr2004 Supplement, Vol. 3, pS81-S95. 1p. 4 Diagrams, 5 Graphs.
Publication Year :
2004

Abstract

In the past few years, artificial neural networks (ANNs) have been used in describing and modelling wastewater treatment processes. Artificial neural network models can be identified without a detailed knowledge of the kinetics of the system to be modelled. Also, ANN models can potentially contain a great deal of information about the system itself, including the same type of information contained in conventional deterministic models. The fact that these models can be continuously updated with minimal resource requirements makes them very attractive for application in a real-time control scenario. In the current paper, applications of ANNs in the field of wastewater treatment performance prediction are reviewed. In addition, this paper presents a case study that reports some comprehensive modelling work to develop nonlinear neural network prediction models for the Gold Bar Wastewater Treatment Plant (GBWWTP), the largest sewage treatment facility in Edmonton, Alberta. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14962551
Volume :
3
Database :
Academic Search Index
Journal :
Journal of Environmental Engineering & Science
Publication Type :
Academic Journal
Accession number :
12922854
Full Text :
https://doi.org/10.1139/S03-067