Runoff Modelling in Urban Storm Drainage by Neural Networks

Michael R. Rasmussen, Michael Brorsen, Kjeld Schaarup-Jensen

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

Abstract

A neural network is used to simulate folw and water levels in a sewer system. The calibration of th neural network is based on a few measured events and the network is validated against measureed events as well as flow simulated with the MOUSE model (Lindberg and Joergensen, 1986). The neural network is used to compute flow or water level at selected points in the sewer system, and to forecast the flow from a small residential area. The main advantages of the neural network are the build-in self calibration procedure and high speed performance, but the neural network cannot be used to extract knowledge of the runoff process. The neural network was found to simulate 150 times faster than e.g. the MOUSE model.
OriginalsprogEngelsk
TitelNOVATECH 95 : 2nd International Conference on Innovative Technologies in Urban Storm Drainage
Antal sider8
ForlagGRAIE
Publikationsdato1995
Sider395-402
ISBN (Trykt)295093370X
StatusUdgivet - 1995
BegivenhedInternational Conference on Innovative Technologies in Urban Storm Drainage - Lyon, Frankrig
Varighed: 30 maj 19951 jun. 1995
Konferencens nummer: 2

Konference

KonferenceInternational Conference on Innovative Technologies in Urban Storm Drainage
Nummer2
Land/OmrådeFrankrig
ByLyon
Periode30/05/199501/06/1995

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