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Issue Date
Title
Author(s)
2006
Critical values of a kernel density-based mutual information estimator
May, R.
;
Dandy, G.
;
Maier, H.
;
Fernando, T.
;
Yen, G.
;
International Joint Conference on Neural Networks (2006 : Vancouver, Canada)
2011
Evaluating parameter sensitivity for surface water modelling of ungauged catchments
Gibbs, M.
;
Dandy, G.
;
Maier, H.
;
IAHR World Congress (34th : 2011 : Brisbane, Australia)
2003
Data transformation for neural network models in water resources applications
Bowden, G.
;
Dandy, G.
;
Maier, H.
2010
Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions
Maier, H.
;
Jain, A.
;
Dandy, G.
;
Sudheer, K.
2010
The response of freshwater plants to salinity pulses
Goodman, A.
;
Ganf, G.
;
Dandy, G.
;
Maier, H.
;
Gibbs, M.
2003
Use of artificial neural networks for modelling chlorine residuals in water distribution systems
Gibbs, M.
;
Morgan, N.
;
Maier, H.
;
Dandy, G.
;
Holmes, M.
;
Nixon, J.
;
Post, D.
;
International Congress on Modelling and Simulation (15th : 2003 : Townsville, Queensland)
2004
Applying fitness landscape measures to water distribution optimization problems
Gibbs, M.
;
Maier, H.
;
Dandy, G.
;
Liong, S.
;
Phoon, K.
;
Babovic, V.
;
International Conference on Hydroinformatics (2004 : Singapore)
2009
Sustainability trade-offs in the planning and design of cluster scale greywater reuse systems
Harnett, L.
;
Nicolson, J.
;
Tennant, R.
;
Dandy, G.
;
Maier, H.
;
Anderssen, R.S.
;
Braddock, R.D.
;
Newham, L.T.H.
;
World IMACS and MODSIM09 International Congress (18th : 2009 : Cairns, Qld)
2011
Runoff and salt transport modelling to maximise environmental outcomes in the upper south east of South Australia
Gibbs, M.
;
Maier, H.
;
Dandy, G.
;
Chan, F.
;
Marinova, D.
;
Anderssen, R.S.
;
International Congress on Modelling and Simulation (19th : 2011 : Perth, Australia)
2009
Selection of input variables for data driven models: An average shifted histogram partial mutual information estimator approach
Fernando, T.
;
Maier, H.
;
Dandy, G.
Discover
Author
22
Gibbs, M.
15
Bowden, G.
14
Nixon, J.
11
May, R.
10
Anderssen, R.S.
6
Braddock, R.D.
6
Broad, D.
6
Fernando, T.
6
Holmes, M.
6
Newham, L.T.H.
.
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Subject
8
Artificial neural networks
4
Forecasting
4
Salinity
4
sustainability
3
artificial neural network
3
uncertainty
3
water quality
2
Australia
2
Baseflow separation
2
Calibration
.
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Date issued
31
2010 - 2016
61
2000 - 2009
2
1997 - 1999