Use of artificial neural networks for modelling multivariate water quality times series / by Holger Robert Maier.
Date
1995
Authors
Maier, Holger R.
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Journal Title
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Type:
Thesis
Citation
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Abstract
This research analyses the suitability of back-propagation artifical neural networks (ANNs) for modelling multivariate water quality time series. The ANNs are successfully applied to two case studies, the long-term forcasting of salinity and the modelling of blue-green algae, in the River Murray, Australia.
School/Discipline
Dept. of Civil and Environmental Engineering
Dissertation Note
Thesis (Ph.D.)--University of Adelaide, Dept. of Civil and Environmental Engineering, 1996?
Provenance
This electronic version is made publicly available by the University of Adelaide in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exception. If you are the author of this thesis and do not wish it to be made publicly available or If you are the owner of any included third party copyright material you wish to be removed from this electronic version, please complete the take down form located at: http://www.adelaide.edu.au/legals
Description
Corrigenda attached to back end paper.
Bibliography: p. 526-559.
xxx, 559 p. : ill. ; 30 cm.
Bibliography: p. 526-559.
xxx, 559 p. : ill. ; 30 cm.