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Selection of input variables for data driven models: An average shifted histogram partial mutual information estimator approach
Selection of input variables for data driven models: An average shifted histogram partial mutual information estimator approach
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Selection of input variables for data driven models: An average shifted histogram partial mutual information estimator approach

Fernando, T.M.K.G. ; Maier, H.R. ; Dandy, G.C.

Journal of hydrology (Amsterdam), 2009-04, Vol.367 (3), p.165-176 [Periódico revisado por pares]

Kidlington: Elsevier B.V

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2
Comparison of Genetic Algorithm Parameter Setting Methods for Chlorine Injection Optimization
Comparison of Genetic Algorithm Parameter Setting Methods for Chlorine Injection Optimization
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Comparison of Genetic Algorithm Parameter Setting Methods for Chlorine Injection Optimization

Gibbs, M. S ; Maier, H. R ; Dandy, G. C

Journal of water resources planning and management, 2010-03, Vol.136 (2), p.288-291 [Periódico revisado por pares]

American Society of Civil Engineers

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3
Input determination for neural network models in water resources applications. Part 1—background and methodology
Input determination for neural network models in water resources applications. Part 1—background and methodology
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Input determination for neural network models in water resources applications. Part 1—background and methodology

Bowden, Gavin J. ; Dandy, Graeme C. ; Maier, Holger R.

Journal of hydrology (Amsterdam), 2005-01, Vol.301 (1), p.75-92 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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4
Calibration and validation of neural networks to ensure physically plausible hydrological modeling
Calibration and validation of neural networks to ensure physically plausible hydrological modeling
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Calibration and validation of neural networks to ensure physically plausible hydrological modeling

Kingston, Greer B. ; Maier, Holger R. ; Lambert, Martin F.

Journal of hydrology (Amsterdam), 2005-11, Vol.314 (1), p.158-176 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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5
Input determination for neural network models in water resources applications. Part 2. Case study: forecasting salinity in a river
Input determination for neural network models in water resources applications. Part 2. Case study: forecasting salinity in a river
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Input determination for neural network models in water resources applications. Part 2. Case study: forecasting salinity in a river

Bowden, Gavin J. ; Maier, Holger R. ; Dandy, Graeme C.

Journal of hydrology (Amsterdam), 2005-01, Vol.301 (1), p.93-107 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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6
Genetic Algorithms for Reliability-Based Optimization of Water Distribution Systems
Genetic Algorithms for Reliability-Based Optimization of Water Distribution Systems
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Genetic Algorithms for Reliability-Based Optimization of Water Distribution Systems

Tolson, Bryan A ; Maier, Holger R ; Simpson, Angus R ; Lence, Barbara J

Journal of water resources planning and management, 2004-01, Vol.130 (1), p.63-72 [Periódico revisado por pares]

American Society of Civil Engineers

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7
Forecasting Cyanobacterial Concentrations Using B-Spline Networks
Forecasting Cyanobacterial Concentrations Using B-Spline Networks
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Forecasting Cyanobacterial Concentrations Using B-Spline Networks

Maier, Holger R ; Sayed, Tarek ; Lence, Barbara J

Journal of computing in civil engineering, 2000-07, Vol.14 (3), p.183-189 [Periódico revisado por pares]

Reston, VA: American Society of Civil Engineers

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8
Ant Colony Optimization Applied to Water Distribution System Design: Comparative Study of Five Algorithms
Ant Colony Optimization Applied to Water Distribution System Design: Comparative Study of Five Algorithms
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Ant Colony Optimization Applied to Water Distribution System Design: Comparative Study of Five Algorithms

Zecchin, Aaron C ; Maier, Holger R ; Simpson, Angus R ; Leonard, Michael ; Nixon, John B

Journal of water resources planning and management, 2007-01, Vol.133 (1), p.87-92 [Periódico revisado por pares]

American Society of Civil Engineers

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