We have been using an innovative computational approach for optimal groundwater management which involves use of artificial neural networks (ANNs) and the genetic algorithm (GA). In this approach, the ANN is trained to predict a particular aspect of the outcome of the flow and transport simulation. Then the.GA directs a search, based on the mechanics of genetics and natural selection, through possible management solutions, in this case patterns or realizations of pumping. These pumping realizations are presented to the trained ANN which predicts the outcome of the pumping realizations. The primary advantages of the ANN approach are parallel processing for the flow and transport simulations and the ability to ''recycle'' or reuse the base of knowledge formed by these flow and transport simulations.


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    Titel :

    Network dissection of neural networks used in optimal groundwater remediation


    Beteiligte:
    L. L. Rogers (Autor:in) / V. M. Johnson (Autor:in) / F. U. Dowla (Autor:in)

    Erscheinungsdatum :

    1992


    Format / Umfang :

    17 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch





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