Applications of Artificial Neural Networks in integrated water management : fiction or future?

An Artificial Neural Network (ANN) is nowadays recognized as a very promising tool for relating input data to output data. It is said that the possibilities of artificial neural networks are unlimited. Here we focus on the potential role of neural networks in integrated water management. An Artifici...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:Water science and technology : a journal of the International Association on Water Pollution Research. - 1986. - 52(2005), 9 vom: 05., Seite 21-31
1. Verfasser: Schulze, F H (VerfasserIn)
Weitere Verfasser: Wolf, H, Jansen, H W, van der Veer, P
Format: Aufsatz
Sprache:English
Veröffentlicht: 2005
Zugriff auf das übergeordnete Werk:Water science and technology : a journal of the International Association on Water Pollution Research
Schlagworte:Journal Article Sewage
LEADER 01000naa a22002652 4500
001 NLM160405785
003 DE-627
005 20231223090038.0
007 tu
008 231223s2005 xx ||||| 00| ||eng c
028 5 2 |a pubmed24n0535.xml 
035 |a (DE-627)NLM160405785 
035 |a (NLM)16445170 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Schulze, F H  |e verfasserin  |4 aut 
245 1 0 |a Applications of Artificial Neural Networks in integrated water management  |b fiction or future? 
264 1 |c 2005 
336 |a Text  |b txt  |2 rdacontent 
337 |a ohne Hilfsmittel zu benutzen  |b n  |2 rdamedia 
338 |a Band  |b nc  |2 rdacarrier 
500 |a Date Completed 07.03.2006 
500 |a Date Revised 10.12.2019 
500 |a published: Print 
500 |a Citation Status MEDLINE 
520 |a An Artificial Neural Network (ANN) is nowadays recognized as a very promising tool for relating input data to output data. It is said that the possibilities of artificial neural networks are unlimited. Here we focus on the potential role of neural networks in integrated water management. An Artificial Neural Network (ANN) is a mathematical methodology which describes relations between cause (input data) and effects (output data) irrespective of the process laying behind and without the need for making assumptions considering the nature of the relations. The applications are widespread and vary from optimization of measuring networks, operational water management, prediction of drinking water consumption, on-line steering of wastewater treatment plants and sewage systems, up to more specific applications such as establishing a relationship between the observed erosion of groyne field sediments and the characteristics of passing vessels on the river Rhine. Especially where processes are complex, neural networks can open new possibilities for understanding and modelling these kinds of complex processes. Besides explaining the method of ANN this paper shows different applications. Three examples have been worked out in more detail. An intelligent monitoring system is shown for the on-line prediction of water consumption, ANN are successfully used for sludge cost monitoring and optimizing wastewater treatment and the usage of ANN is shown in optimizing and monitoring water quality measuring networks. An ANN appears to be a multiuse and powerful tool for modelling complex processes 
650 4 |a Journal Article 
650 7 |a Sewage  |2 NLM 
700 1 |a Wolf, H  |e verfasserin  |4 aut 
700 1 |a Jansen, H W  |e verfasserin  |4 aut 
700 1 |a van der Veer, P  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t Water science and technology : a journal of the International Association on Water Pollution Research  |d 1986  |g 52(2005), 9 vom: 05., Seite 21-31  |w (DE-627)NLM098149431  |x 0273-1223  |7 nnns 
773 1 8 |g volume:52  |g year:2005  |g number:9  |g day:05  |g pages:21-31 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 52  |j 2005  |e 9  |b 05  |h 21-31