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Neural networks complemented with genetic algorithms and fuzzy systems for predicting nitrogenous effluent variables in wastewater treatment plants

This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen

© WSEAS Transactions on Systems and Control, 2008, vol.7, núm. 6, p. 695-705

World Scientific and Engineering Academy and Society (WSEAS)

Author: Clara i Lloret, Narcís
Date: 2008
Abstract: This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen
Format: application/pdf
ISSN: 1991-8763 (versió paper)
2224-2856 (versió electrònica)
Document access: http://hdl.handle.net/10256/8983
Language: eng
Publisher: World Scientific and Engineering Academy and Society (WSEAS)
Collection: Reproducció digital del document publicat a: http://dl.acm.org/citation.cfm?id=1456035&CFID=426373287&CFTOKEN=19370478
Articles publicats (D-IMA)
Is part of: © WSEAS Transactions on Systems and Control, 2008, vol.7, núm. 6, p. 695-705
Rights: Tots els drets reservats
Subject: Xarxes neuronals (Informàtica)
Neural networks (Computer science)
Title: Neural networks complemented with genetic algorithms and fuzzy systems for predicting nitrogenous effluent variables in wastewater treatment plants
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

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