Using neutral networks for waste-water purification
| dc.contributor.author | Venema, R. S. | |
| dc.contributor.author | Bron, J. | |
| dc.contributor.author | Zijlstra, R.M. | |
| dc.contributor.author | Nijhuis, J. A. G. | |
| dc.contributor.author | Spaanenburg, L. | |
| dc.contributor.editor | Haasis, H.-D. | |
| dc.contributor.editor | Ranze, K.C. | |
| dc.date.accessioned | 2019-09-16T09:30:52Z | |
| dc.date.available | 2019-09-16T09:30:52Z | |
| dc.date.issued | 1998 | |
| dc.description.abstract | 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. | de |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/26510 | |
| dc.publisher | Metropolis | |
| dc.relation.ispartof | Umweltinformatik ’98 - Vernetzte Strukturen in Informatik, Umwelt und Wirtschaft - Computer Science for Environmental Protection ’98 - Networked Structures in Information Technology, the Environment and Business | |
| dc.relation.ispartofseries | EnviroInfo | |
| dc.title | Using neutral networks for waste-water purification | de |
| dc.type | Text/Conference Paper | |
| gi.citation.publisherPlace | Marburg | |
| gi.conference.date | 1998 | |
| gi.conference.location | Bremen | |
| gi.conference.sessiontitle | Wissensverarbeitung in Umweltanwendungen, Knowledge Processing for Environmental Applications |