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dc.contributor.authorSayers, W.
dc.contributor.authorSavic, Dragan
dc.contributor.authorKapelan, Zoran
dc.contributor.authorKellagher, Richard
dc.date.accessioned2014-09-04T12:06:10Z
dc.date.issued2014-04-23
dc.description.abstractUrban flooding is estimated to cause £270 million pounds worth of damage each year in England and Wales alone. There has, therefore, been a clear need to develop improved methods of identifying intervention strategies to reduce flood risk in urban environments. This paper describes ground-work performed towards evaluating the relative suitability of several algorithms applied to multi-objective optimisation of flood risk intervention strategies in an urban drainage network. An effective methodology is described for reducing an array of return period/duration rainfall files to a minimum, and it is described how this methodology makes possible comparisons of optimisation algorithms. This work has been undertaken as part of a STREAM-IDC EngD project which is a collaborative effort between the University of Exeter, and HR Wallingford.en_GB
dc.identifier.citationVol. 70, pp. 1505 - 1512en_GB
dc.identifier.doi10.1016/j.proeng.2014.02.165
dc.identifier.urihttp://hdl.handle.net/10871/15436
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.rightsPublished under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) licence: http://creativecommons.org/licenses/by-nc-nd/3.0/en_GB
dc.subjectInnovationen_GB
dc.subjectTechnologyen_GB
dc.subjectMulti-objectiveen_GB
dc.subjectOptimisationen_GB
dc.subjectOptimizationen_GB
dc.subjectDrainageen_GB
dc.subjectFloodsen_GB
dc.subjectFloodingen_GB
dc.titleArtificial intelligence techniques for flood risk management in urban environmentsen_GB
dc.typeArticleen_GB
dc.date.available2014-09-04T12:06:10Z
dc.identifier.issn1877-7058
dc.descriptionCopyright © 2013 The Authors. Published by Elsevier Ltd.en_GB
dc.description12th International Conference on Computing and Control for the Water Industry, CCWI2013en_GB
dc.identifier.journalProcedia Engineeringen_GB


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