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PreviewIssue DateTitleAuthor(s)
2014An evaluation framework for input variable selection algorithms for environmental data-driven modelsGalelli, S.; Humphrey, G.; Maier, H.; Castelletti, A.; Dandy, G.; Gibbs, M.
2000Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applicationsMaier, H.; Dandy, G.
2005Input determination for neural network models in water resources applications. Part 2. Case study: forecasting salinity in a riverBowden, G.; Maier, H.; Dandy, G.
2005Input determination for neural network models in water resources applications. Part 1 - background and methodologyBowden, G.; Dandy, G.; Maier, H.
2014Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directionsMaier, H.; Kapelan, Z.; Kasprzyk, J.; Kollat, J.; Matott, L.; Cunha, M.; Dandy, G.; Gibbs, M.; Keedwell, E.; Marchi, A.; Ostfeld, A.; Savic, D.; Solomatine, D.; Vrugt, J.; Zecchin, A.; Minsker, B.; Barbour, E.; Kuczera, G.; Pasha, F.; Castelletti, A.; et al.
2008Non-linear variable selection for artificial neural networks using partial mutual informationMay, R.; Maier, H.; Dandy, G.; Fernando, T.
2010Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directionsMaier, H.; Jain, A.; Dandy, G.; Sudheer, K.
2008Application of partial mutual information variable selection to ANN forecasting of water quality in water distribution systemsMay, R.; Dandy, G.; Maier, H.; Nixon, J.
2013Relative magnitudes of sources of uncertainty in assessing climate change impacts on water supply security for the southern Adelaide water supply systemPaton, F.; Maier, H.; Dandy, G.
2015Adaptive, multiobjective optimal sequencing approach for urban water supply augmentation under deep uncertaintyBeh, E.; Maier, H.; Dandy, G.