Search Results - Abrahart, R.J.

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  1. 1
    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, N.J., Maier, H.R., Toth, E., Elshorbagy, A., Solomatine, D., Chang, F.-J., Abrahart, R.J.

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  2. 2
    Flood estimation at ungauged sites using artificial neural networks

    Flood estimation at ungauged sites using artificial neural networks by Dawson, C.W., Abrahart, R.J., Shamseldin, A.Y., Wilby, R.L.

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  3. 3
    HydroTest: A web-based toolbox of evaluation metrics for the standardised assessment of hydrological forecasts

    HydroTest: A web-based toolbox of evaluation metrics for the standardised assessment of hydrological forecasts by Dawson, C.W., Abrahart, R.J., See, L.M.

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  4. 4
    Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting

    Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting by 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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  5. 5
    Discussion of “River flow estimation from upstream flow records by artificial intelligence methods” by M.E. Turan, M.A. Yurdusev [J. Hydrol. 369 (2009) 71–77]

    Discussion of “River flow estimation from upstream flow records by artificial intelligence methods” by M.E. Turan, M.A. Yurdusev [J. Hydrol. 369 (2009) 71–77] by Mount, N.J., Abrahart, R.J.

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  6. 6
    Neural network modelling of non-linear hydrological relationships

    Neural network modelling of non-linear hydrological relationships by Abrahart, R.J, See, L.M

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  7. 7
    HydroTest: Further development of a web resource for the standardised assessment of hydrological models

    HydroTest: Further development of a web resource for the standardised assessment of hydrological models by Dawson, C.W., Abrahart, R.J., See, L.M.

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  8. 8
    Modelling sediment transfer in Malawi: comparing backpropagation neural network solutions against a multiple linear regression benchmark using small data sets

    Modelling sediment transfer in Malawi: comparing backpropagation neural network solutions against a multiple linear regression benchmark using small data sets by Abrahart, R.J., White, S.M.

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  9. 9
    A comparative study of artificial neural network techniques for river stage forecasting

    A comparative study of artificial neural network techniques for river stage forecasting by Dawson, C.W., See, L.M., Abrahart, R.J., Wilby, R.L., Shamseldin, A.Y., Anctil, F., Belbachir, A.N., Bowden, G., Dandy, G., Lauzon, N., Maier, H.

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  10. 10
    Neurohydrology: implementation options and a research agenda

    Neurohydrology: implementation options and a research agenda by Abrahart, Robert J

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  11. 11
    Fusing multi-model hydrological data

    Fusing multi-model hydrological data by Abrahart, R.J., See, L.

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  12. 12
    Neural network modelling of the 20-year flood event for catchments across the UK

    Neural network modelling of the 20-year flood event for catchments across the UK by Dawson, C.W., Abrahart, R.J., Shamseldin, A.Y., Wilby, R.L., See, L.M.

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  13. 13
    Neural network river discharge forecasters: an empirical investigation of hidden unit processing functions based on two different catchments

    Neural network river discharge forecasters: an empirical investigation of hidden unit processing functions based on two different catchments by Shamseldin, A.Y., Abrahart, R.J., See, L.M.

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