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Results 21-29 of 29 (Search time: 0.002 seconds).
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Issue Date
Title
Author(s)
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.
2005
Calibration and validation of neural networks to ensure physically plausible hydrological modeling
Humphrey, G.
;
Maier, H.
;
Lambert, M.
2005
A Bayesian approach to artificial neural network model selection
Humphrey, G.
;
Maier, H.
;
Lambert, M.
;
Zerger, A.
;
Argent, R.
;
International Congress on Modelling and Simulation (16th : 2005 : Melbourne, Victoria)
2005
A parameter-bounding approach to sensitivity assessment of large simulation models
Norton, J.
;
Chiew, F.
;
Dandy, G.
;
Maier, H.
;
Zerger, A.
;
Argent, R.
;
International Congress on Modelling and Simulation (16th : 2005 : Melbourne, Victoria)
2005
Estimating risk measures for water distribution systems using metamodels
Broad, D.
;
Maier, H.
;
Dandy, G.
;
Nixon, J.
;
World Water & Environmental Resources Congress (2005 : Anchorage, Alaska)
2005
Selection of genetic algorithm parameters for water distribution system optimization
Gibbs, M.
;
Dandy, G.
;
Maier, H.
;
Nixon, J.
;
World Water & Environmental Resources Congress (2005 : Anchorage, Alaska)
2005
Efficient selection of inputs for artificial neural network models
Fernando, T.
;
Maier, H.
;
Dandy, G.
;
May, R.
;
Zerger, A.
;
Argent, R.
;
International Congress on Modelling and Simulation (16th : 2005 : Melbourne, Victoria)
2005
A comparison of sensitivity analysis techniques for complex models for environment management
Ravalico, J.
;
Maier, H.
;
Dandy, G.
;
Norton, J.
;
Croke, B.
;
Zerger, A.
;
Argent, R.
;
International Congress on Modelling and Simulation (16th : 2005 : Melbourne, Victoria)
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Author
13
Dandy, G.
9
Argent, R.
9
International Congress on Modelli...
9
Zerger, A.
4
Bowden, G.
4
Humphrey, G.
4
Lambert, M.
4
Nixon, J.
4
Simpson, A.
3
Foong, W.
.
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Subject
3
Artificial neural networks
2
Input determination
2
Markov chain Monte Carlo
2
Neural networks
1
Ant colony optimization
1
Ant colony optimization (ACO)
1
artificial neural network
1
artificial neural networks
1
Artificial neural networks
1
Bayesian estimation
.
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