The simulation of runoff from a Himalayan Glacier basin using an Artificial Neural Network (ANN) is presented. The performance of the ANN model is found to be superior to the Energy Balance Model and the Multiple Regression model. The RMS Error is used as the figure of merit for judging the performance of the three models, and the RMS Error for the ANN model is the latest of the three models. The ANN is faster in learning and exhibits excellent system generalization characteristics.


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    Title :

    Application of artificial neural networks in hydrological modeling: A case study of runoff simulation of a Himalayan glacier basin


    Contributors:
    Buch, A. M. (author) / Narain, A. (author) / Pandey, P. C. (author)


    Publication date :

    1994-05-01


    Type of media :

    Conference paper


    Type of material :

    No indication


    Language :

    English


    Keywords :


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