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Preview	Issue Date	Title	Author(s)
	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.
	2008	AI techniques for hydrological Modeling and mangement. II: Optimization	Humphrey, G.; Dandy, G.; Maier, H.; Robinson, L.
	2006	Minimum number of generations required for convergence of genetic algorithms	Gibbs, M.; Maier, H.; Dandy, G.; Nixon, J.; Yen, G.; IEEE Congress on Evolutionary Computation (2006 : Vancouver, B.C.)
	2006	Improving metamodel-based optimization of water distribution systems with local search	Broad, D.; Dandy, G.; Maier, H.; Nixon, J.; Yen, G.; IEEE Congress on Evolutionary Computation (2006 : Vancouver, B.C.)
	2004	A metamodeling approach to water distribution system optimization	Broad, D.; Dandy, G.; Maier, H.; World Water and Environmental Resources Congress (2004 : Salt Lake City, Utah)
	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)