A Neutral Network Approach to Rainfall Forecasting in urban environments

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dc.contributor.author Ball, James en_US
dc.contributor.author Luk, K en_US
dc.contributor.editor Robert J. Abrahart, Pauline E. Kneale, Linda M. See en_US
dc.date.accessioned 2010-05-28T09:38:30Z
dc.date.available 2010-05-28T09:38:30Z
dc.date.issued 2004 en_US
dc.identifier 2006008644 en_US
dc.identifier.citation Ball James and Luk K 2004, 'A Neutral Network Approach to Rainfall Forecasting in urban environments', in NA (ed.), AA Balkema Publishers, Leiden, The Netherlands, pp. 177-195. en_US
dc.identifier.issn 90-5809-619-x en_US
dc.identifier.other B1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/7886
dc.description.abstract An effective flood warning system in urban areas must provide the warnign with sufficient lead time for an appropriate response by the relevant emergency services and the affected community. The requirement poses a critical problem as most urban catchments are characterised by a fast hydrologic response to storm events. The approach used here to forecast rainfall over the Upper Paramatta River Catchment in Sydney is based on the application of a pattern recognition technique using an artificial neural network. It assumes that the future rainfall is a function of a discrete number of past spatial and temporal rainfall records; an important task, therefore, is the determination of the number of spatial and temporal rainfall records necessary for accurate prediction of future rainfall. The rainfall prediction model performed best when an optimal amount of spatial and temporal rainfall information was provided to the network. en_US
dc.language en_US
dc.publisher AA Balkema Publishers en_US
dc.relation.isbasedon NA en_US
dc.title A Neutral Network Approach to Rainfall Forecasting in urban environments en_US
dc.parent Neural networks for hydrological modelling en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Leiden, The Netherlands en_US
dc.identifier.startpage 177 en_US
dc.identifier.endpage 195 en_US
dc.cauo.name FEIT.School of Civil and Environmental Engineering en_US
dc.conference Verified OK en_US
dc.for 090509 en_US
dc.personcode 997686 en_US
dc.personcode 0000031701 en_US
dc.percentage 60 en_US
dc.classification.name Water Resources Engineering en_US
dc.classification.type FOR-08 en_US
dc.edition 1 en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords NA en_US


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