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Preview	Issue Date	Title	Author(s)
	2009	Rainfall runoff modelling using neural networks: state-of-the-art and future research needs	Jain, A.; Maier, H.; Dandy, G.; Sudheer, K.
	2011	Relationship between problem characteristics and the optimal number of genetic algorithm generations	Gibbs, M.; Maier, H.; Dandy, G.
	2010	Evaluation of parameter setting for two GIS based unit hydrograph models	Gibbs, M.; Dandy, G.; Maier, H.
	2011	An integrated dynamic modeling framework for investigating the impact of climate change and variability on irrigated agriculture	Rowan, T.; Maier, H.; Connor, J.; Dandy, G.
	1998	Use of Artificial Neural Networks for Modelling Cyanobacteria Anabaena spp. in the River Murray, South Australia	Maier, H.; Dandy, G.; Burch, M.
	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.
	2010	Comparison of genetic algorithm parameter setting methods for chlorine injection optimization	Gibbs, M.; Maier, H.; Dandy, G.