1. Adelaide Research & Scholarship
  2. Schools and Disciplines
  3. School of Civil, Environmental and Mining Engineering
  4. Civil and Environmental Engineering publications
Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/958
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMaier, Holger R.en
dc.contributor.authorDandy, Graeme Clydeen
dc.date.issued1998en
dc.identifier.citationEnvironmental Modelling and Software. 13(2):179-191en
dc.identifier.issn1364-8152en
dc.identifier.urihttp://hdl.handle.net/2440/958-
dc.language.isoenen
dc.titleUnderstanding the behaviour and optimising the performance of back-propagation neural networks : an empirical studyen
dc.typeJournal articleen
Appears in Collections:Civil and Environmental Engineering publications
Environment Institute publications

Files in This Item:
There are no files associated with this item.
Show simple item record


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.