Estimation of Chemical Oxygen Demand by Ultraviolet Spectroscopic Profiling and Artificial Neural Networks

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Title Estimation of Chemical Oxygen Demand by Ultraviolet Spectroscopic Profiling and Artificial Neural Networks
Author Fogelman, Shoshana; Blumenstein, Michael Myer; Zhao, Huijun
Journal Name Neural Computing And Applications
Year Published 2006
Place of publication United Kingdom
Publisher Springer
Abstract A simple method based on the mathematical treatment of spectral absorbance profiles in conjunction with artificial neural networks (ANNs) is demonstrated for rapidly estimating chemical oxygen demand (COD) values of wastewater samples. In order to improve spectroscopic analysis and ANN training time as well as to reduce the storage space of the trained ANN algorithm, it is necessary to decrease the ANN input vector size by extracting unique characteristics from the raw input pattern. Key features from the spectral absorbance pattern were therefore selected to obtain the spectral absorbance profile, reducing the ANN input vector from 160 to 10 selected inputs. The results indicate that the COD values obtained from the selected absorbance profiles agreed well with those obtained from the entire absorbance pattern. The spectral absorbance profile technique was also compared to COD values estimated by a multiple linear regression (MLR) model to validate whether ANNs were better and more robust models for rapid COD analysis. It was found that the ANN model predicted COD values closer to standard COD values than the MLR model.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1007/s00521-005-0015-9
Volume 15
Page from 197
Page to 203
ISSN 0941-0643
Date Accessioned 2007-03-01
Language en_AU
Research Centre Environmental Futures Research Institute; Institute for Integrated and Intelligent Systems
Faculty Faculty of Environmental Sciences
Subject PRE2009-Sensor (Chemical and Bio-) Technology
URI http://hdl.handle.net/10072/13804
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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