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      Application of neural networks to modelling nonlinear relationships in ecology

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      Ecological Modelling

      Elsevier BV

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          Learning representations by back-propagating errors

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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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                Author and article information

                Journal
                Ecological Modelling
                Ecological Modelling
                Elsevier BV
                03043800
                September 1996
                September 1996
                : 90
                : 1
                : 39-52
                Article
                10.1016/0304-3800(95)00142-5
                © 1996

                http://www.elsevier.com/tdm/userlicense/1.0/

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