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      Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications

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      Environmental Modelling & Software

      Elsevier BV

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          Most cited references 129

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          Multilayer feedforward networks are universal approximators

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            Identification and control of dynamical systems using neural networks.

            It is demonstrated that neural networks can be used effectively for the identification and control of nonlinear dynamical systems. The emphasis is on models for both identification and control. Static and dynamic backpropagation methods for the adjustment of parameters are discussed. In the models that are introduced, multilayer and recurrent networks are interconnected in novel configurations, and hence there is a real need to study them in a unified fashion. Simulation results reveal that the identification and adaptive control schemes suggested are practically feasible. Basic concepts and definitions are introduced throughout, and theoretical questions that have to be addressed are also described.
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              A scaled conjugate gradient algorithm for fast supervised learning

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                Author and article information

                Journal
                Environmental Modelling & Software
                Environmental Modelling & Software
                Elsevier BV
                13648152
                January 2000
                January 2000
                : 15
                : 1
                : 101-124
                Article
                10.1016/S1364-8152(99)00007-9
                © 2000

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