Use of recurrent neural networks and hybrid evolutionary algorithms for the prediction of phytoplankton abundance and succession before and after eutrophication control of two shallow lakes

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dc.contributor.authorTalib, A.
dc.contributor.authorRecknagel, F.
dc.contributor.authorCao, H.
dc.contributor.authorvan der Molen, D.
dc.contributor.conferenceInternational Congress on Modelling and Simulation (16th : 2005 : Melbourne, Victoria)
dc.contributor.editorZerger, A.
dc.contributor.editorArgent, R.
dc.date.issued2005
dc.identifier.citationProceedings of the international congress on modelling and simulation, 12 December, 2005
dc.identifier.isbn0975840002
dc.identifier.orcidRecknagel, F. [0000-0002-1028-9413]
dc.identifier.urihttp://hdl.handle.net/2440/28311
dc.language.isoen
dc.publisherModelling & Simulation Society of Australia & New Zealand Inc.
dc.publisher.placehttp://mssanz.org.au/modsim05/papers/talib.pdf
dc.titleUse of recurrent neural networks and hybrid evolutionary algorithms for the prediction of phytoplankton abundance and succession before and after eutrophication control of two shallow lakes
dc.typeConference paper
pubs.publication-statusPublished

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