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    Water flows modelling and forecasting using a RBF neural network
    (Universidad Icesi, 2008-12-17) Fajardo Toro, Carlos Hernán; Fernández Riverola, Florentino; Soto González, Benedicto; González Peña, Daniel
    A hydrologic estimation model base on the utilization of radial basis function neural networks is presented, in which the aim is to forecast stream flows in an automated fashion. The problem of river flow forecasting is a non-trivial task because (i) the various physical mechanisms governing the river flow dynamics act on a wide range of temporal and spatial scales and (ii) almost all mechanisms involved in the river flow process present some degree of nonlinearity. The proposed neural network was used to forecast daily river discharges in a river basin providing satisfactory results and outperforming previous.