Use of Gene Expression Programming for Multimodel Combination of Rainfall-Runoff Models von Fernando, Achela K, Shamseldin, Asaad Y, Abrahart, Robert J

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Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting von Abrahart, Robert J., Anctil, François, Coulibaly, Paulin, Dawson, Christian W., Mount, Nick J., See, Linda M., Shamseldin, Asaad Y., Solomatine, Dimitri P., Toth, Elena, Wilby, Robert L.

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Improved validation framework and R-package for artificial neural network models von Humphrey, Greer B., Maier, Holger R., Wu, Wenyan, Mount, Nick J., Dandy, Graeme C., Abrahart, Robert J., Dawson, Christian W.

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Symbiotic adaptive neuro-evolution applied to rainfall–runoff modelling in northern England von Dawson, Christian W., See, Linda M., Abrahart, Robert J., Heppenstall, Alison J.

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Including spatial distribution in a data-driven rainfall-runoff model to improve reservoir inflow forecasting in Taiwan von Tsai, Meng-Jung, Abrahart, Robert J., Mount, Nick J., Chang, Fi-John

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Load or concentration, logged or unlogged? Addressing ten years of uncertainty in neural network suspended sediment prediction von Mount, Nick J., Abrahart, Robert J.

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Comparing neural network and autoregressive moving average techniques for the provision of continuous river flow forecasts in two contrasting catchments von Abrahart, Robert J., See, Linda

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A typology of different development and testing options for symbolic regression modelling of measured and calculated datasets von Beriro, Darren J., Abrahart, Robert J., Nathanail, C. Paul, Moreno, Jimmy, Bawazir, A. Salim

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Discussion of ‘Reservoir Computing approach to Great Lakes water level forecasting’ by P. Coulibaly [J. Hydrol. 381(2010) 76–88] von Abrahart, Robert J., Mount, Nick J., Shamseldin, Asaad Y.

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DAMP: A protocol for contextualising goodness-of-fit statistics in sediment-discharge data-driven modelling von Abrahart, Robert J., Mount, Nick J., Ab Ghani, Ngahzaifa, Clifford, Nicholas J., Dawson, Christian W.

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GeoComputation von Abrahart, Robert J, See, Linda M

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Neuroemulation: definition and key benefits for water resources research von Abrahart, Robert J, Mount, Nick J, Shamseldin, Asaad Y

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Neuro-fuzzy modelling of suspended sediment load: The need for a sound comparison with established methods von Abrahart, Robert J., Ab Ghani, Ngahzaifa

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Letter to the Editor on “Precipitation Forecasting Using Wavelet-Genetic Programming and Wavelet-Neuro-Fuzzy Conjunction Models” by Ozgur Kisi & Jalal Shiri [Water Resources Manage... von Beriro, Darren J., Abrahart, Robert J., Mount, Nick J., Nathanail, C. Paul

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Multi-model data fusion for hydrological forecasting von See, Linda, Abrahart, Robert J

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Discussion of “Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers” von Abrahart, Robert J, Mount, Nick J

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GeoComputation

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Neural network rainfall-runoff forecasting based on continuous resampling von Abrahart, Robert J

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Investigating the role of saliency analysis with a neural network rainfall-runoff model von Abrahart, Robert J, See, Linda, Kneale, Pauline E

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“Comparison of genetic programming with neuro-fuzzy systems for predicting short-term water table depth fluctuations” by Jalal Shiri & Ozgur Kisi [Computers and Geosciences (2011)... von Beriro, Darren J., Abrahart, Robert J., Paul Nathanail, C.

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