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Issue Date
Title
Author(s)
2006
Investigation into the relationship between chlorine decay and water distribution parameters using data driven methods
Gibbs, M.
;
Morgan, N.
;
Maier, H.
;
Dandy, G.
;
Nixon, J.
;
Holmes, M.
2006
Forecasting chlorine residuals in a water distribution system using a general regression neural network
Bowden, G.
;
Nixon, J.
;
Dandy, G.
;
Maier, H.
;
Holmes, M.
2005
Input determination for neural network models in water resources applications. Part 2. Case study: forecasting salinity in a river
Bowden, G.
;
Maier, H.
;
Dandy, G.
2001
Neural network based modelling of environmental variables: A systematic approach
Maier, H.
;
Dandy, G.
2005
Water distribution system optimization using metamodels
Broad, D.
;
Dandy, G.
;
Maier, H.
2005
Input determination for neural network models in water resources applications. Part 1 - background and methodology
Bowden, G.
;
Dandy, G.
;
Maier, H.
2009
Selection of input variables for data driven models: An average shifted histogram partial mutual information estimator approach
Fernando, T.
;
Maier, H.
;
Dandy, G.
2009
Sensitivity analysis for decision-making using the MORE method-A Pareto approach
Ravalico, J.
;
Maier, H.
;
Dandy, G.
2008
Application of partial mutual information variable selection to ANN forecasting of water quality in water distribution systems
May, R.
;
Dandy, G.
;
Maier, H.
;
Nixon, J.
2008
A genetic algorithm calibration method based on convergence due to genetic drift
Gibbs, M.
;
Dandy, G.
;
Maier, H.
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Author
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Maier, H.
15
Nixon, J.
14
Bowden, G.
12
Gibbs, M.
8
May, R.
6
Anderssen, R.S.
6
Braddock, R.D.
6
Fernando, T.
6
Holmes, M.
6
Newham, L.T.H.
.
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Artificial neural networks
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artificial neural network
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Forecasting
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General regression neural network
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genetic algorithm
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Input determination
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Mutual information
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Optimization
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