Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/86344
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dc.contributor.authorLi, X.en
dc.contributor.authorZecchin, A.en
dc.contributor.authorMaier, H.en
dc.date.issued2014en
dc.identifier.citationEnvironmental Modelling & Software, 2014; 59:162-186en
dc.identifier.issn1364-8152en
dc.identifier.issn1873-6726en
dc.identifier.urihttp://hdl.handle.net/2440/86344-
dc.description.abstractAbstract not availableen
dc.description.statementofresponsibilityXuyuan Li, Aaron C. Zecchin, Holger R. Maieren
dc.language.isoenen
dc.publisherElsevieren
dc.rights© 2014 Elsevier Ltd. All rights reserved.en
dc.subjectGeneral regression neural networks; Smoothing parameter estimators; Artificial neural networks; Multi-layer perceptrons; Extreme and average events; Hydrology and water resourcesen
dc.titleSelection of smoothing parameter estimators for general regression neural networks - applications to hydrological and water resources modellingen
dc.typeJournal articleen
dc.identifier.rmid0030008410en
dc.identifier.doi10.1016/j.envsoft.2014.05.010en
dc.identifier.pubid71026-
pubs.library.collectionCivil and Environmental Engineering publicationsen
pubs.library.teamDS05en
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
dc.identifier.orcidZecchin, A. [0000-0001-8908-7023]en
dc.identifier.orcidMaier, H. [0000-0002-0277-6887]en
Appears in Collections:Civil and Environmental Engineering publications

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