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Preview	Issue Date	Title	Author(s)
	2012	A method for comparing data splitting approaches for developing hydrological ANN models	Wu, W.; May, R.; Dandy, G.; Maier, H.; International Congress on Environmental Modelling and Software (6th : 2012 : Leipzig, Germany)
	2008	Non-linear variable selection for artificial neural networks using partial mutual information	May, R.; Maier, H.; Dandy, G.; Fernando, T.
	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.
	2006	A probabilistic method for assisting knowledge extraction from artificial neural networks used for hydrological prediction	Humphrey, G.; Maier, H.; Lambert, 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	Input determination for neural network models in water resources applications. Part 1 - background and methodology	Bowden, G.; Dandy, G.; Maier, H.
	2010	Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions	Maier, H.; Jain, A.; Dandy, G.; Sudheer, K.
	2009	Selection of input variables for data driven models: An average shifted histogram partial mutual information estimator approach	Fernando, T.; Maier, H.; Dandy, G.
	2005	Calibration and validation of neural networks to ensure physically plausible hydrological modeling	Humphrey, G.; Maier, H.; Lambert, M.