Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/18661
Type: Thesis
Title: Use of artificial neural networks for modelling multivariate water quality times series / by Holger Robert Maier.
Author: Maier, Holger R.
Issue Date: 1995
School/Discipline: Dept. of Civil and Environmental Engineering
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.
Dissertation Note: Thesis (Ph.D.)--University of Adelaide, Dept. of Civil and Environmental Engineering, 1996?
Subject: Neural networks (Computer science)
Water quality Computer simulation.
Salinity Computer simulation.
Cyanobacterial blooms Computer simulation.
Description: Corrigenda attached to back end paper.
Bibliography: p. 526-559.
xxx, 559 p. : ill. ; 30 cm.
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
Appears in Collections:Research Theses

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