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Using neutral networks for waste-water purification
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Text/Conference Paper
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Datum
1998
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Verlag
Metropolis
Zusammenfassung
One of the main issues in the research into a time series is its prediction. Artificial neural networks are suitable for that purpose because of their ability to identify non-linear systems. We illustrate the use of neural networks by a forecasting problem in waste-water purification, namely the prediction of its ammonia concentration. For this application, we used a feedforward architecture with an input delay line. However, because of the multi-variate, multi-scale and multi-stationary properties of the problem, we propose to put modularity in the neural design to capture these dynamics.