Search Results - Abrahart, R.J

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  1. 1
    Legitimising data-driven models: exemplification of a new data-driven mechanistic modelling framework

    Legitimising data-driven models: exemplification of a new data-driven mechanistic modelling framework by Mount, Nick J., Dawson, C.W., Abrahart, R.J.

    Published 2013
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  2. 2
    Neuroemulation: definition and key benefits for water resources research

    Neuroemulation: definition and key benefits for water resources research by Abrahart, R.J., Mount, Nick J., Shamseldin, A.Y.

    Published 2012
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  3. 3
    Legitimising data-driven models: exemplification of a new data-driven mechanistic modelling framework

    Legitimising data-driven models: exemplification of a new data-driven mechanistic modelling framework by Mount, Nick J., Dawson, C.W., Abrahart, R.J.

    Published 2013
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  4. 4
    Including spatial distribution in a data-driven rainfall-runoff model to improve reservoir inflow forecasting in Taiwan

    Including spatial distribution in a data-driven rainfall-runoff model to improve reservoir inflow forecasting in Taiwan by Meng-Jung, T., Abrahart, R.J., Mount, Nick J., Chang, F.-J.

    Published 2014
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  5. 5
    Sensitivity analysis for comparison, validation and physical-legitimacy of neural network-based hydrological models

    Sensitivity analysis for comparison, validation and physical-legitimacy of neural network-based hydrological models by Dawson, C.W., Mount, Nick J., Abrahart, R.J., Louis, J.

    Published 2014
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  6. 6
    Ideal point error for model assessment in data-driven river flow forecasting

    Ideal point error for model assessment in data-driven river flow forecasting by Dawson, C.W, Mount, Nick J., Abrahart, R.J, Shamseldin, A.Y.

    Published 2012
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  7. 7
    The need for operational reasoning in data-driven rating curve prediction of suspended sediment

    The need for operational reasoning in data-driven rating curve prediction of suspended sediment by Mount, Nick J., Abrahart, R.J., Dawson, C.W., Ab Ghani, N.

    Published 2012
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  8. 8
    DAMP: a protocol for contextualising goodness-of-fit statistics in sediment-discharge data-driven modelling

    DAMP: a protocol for contextualising goodness-of-fit statistics in sediment-discharge data-driven modelling by Abrahart, R.J., Mount, Nick J., Ab Ghani, Ngahzaifa, Clifford, Nicholas J., Dawson, C.W.

    Published 2011
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  9. 9
    Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan

    Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan by Mount, Nick J., Maier, Holger R., Toth, Elena, Elshorbagy, Amin, Solomatine, Dimitri, Chang, Fi-John, Abrahart, R.J.

    Published 2016
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  10. 10
    Improved validation framework and R-package for artificial neural network models

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

    Published 2017
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