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Predicting Estuarine Algal Blooms Utilising Neural Network Modelling-A Preliminary Investigation
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Document Date: 2013-01-15 17:51:41


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Company

Oxford University Press / StatSoft Inc. / Prentice-Hall / Pearson / Neural Networks / Artificial Neural Networks / Manly Hydraulics Laboratory / 3Manly Hydraulics Laboratory / /

Country

Australia / /

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Facility

University of New South Wales / University of Adelaide / /

IndustryTerm

backpropogation training algorithm / interconnected processing elements / biological nervous systems / on-line version / back propagation algorithm / data analysis software system / back-propagation training algorithm / Data pre-processing / coastal resource management / web link / predictive tool / back propogation training algorithm / /

NaturalFeature

Calabash Bay / Berowra Estuary / /

Organization

University of Adelaide / Department of Civil and Environmental Engineering / Hornsby Shire Council / Algal Coordinating Committee / Bureau of Meteorology / NSW Department of Land and Water Coanservation / University of New South Wales / Department of Commerce / Oxford University / /

Person

Lee / Ross McPherson / Kristy Guise / David Leggett / Sydney Metropolitan / Huang / /

Position

Governor / Bishop / REFERENCES Bishop / data logger / /

ProvinceOrState

New South Wales / /

Region

South Wales / South Eastern Australia / /

Technology

back-propagation training algorithm / radiation / cellular telephone / 4.0 NETWORK ARCHITECTURE AND LEARNING ALGORITHM / t-1 / Neural Network / backpropogation training algorithm / Environmental Engineering / back propogation training algorithm / back propagation algorithm / been developed utilising a backpropogation training algorithm / /

URL

www.hornsby.nsw.gov.au / /

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