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Using neutral networks for waste-water purification

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.

Beschreibung

Venema, R. S.; Bron, J.; Zijlstra, R.M.; Nijhuis, J. A. G.; Spaanenburg, L. (1998): Using neutral networks for waste-water purification. Umweltinformatik ’98 - Vernetzte Strukturen in Informatik, Umwelt und Wirtschaft - Computer Science for Environmental Protection ’98 - Networked Structures in Information Technology, the Environment and Business. Marburg: Metropolis. Wissensverarbeitung in Umweltanwendungen, Knowledge Processing for Environmental Applications. Bremen. 1998

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