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Article: Neighbourhood selection for local modelling and prediction of hydrological time series

TitleNeighbourhood selection for local modelling and prediction of hydrological time series
Authors
KeywordsChaos
Generalized degrees of freedom
Hydrological time series
Local models
Neighbourhood selection
Issue Date2002
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jhydrol
Citation
Journal Of Hydrology, 2002, v. 258 n. 1-4, p. 40-57 How to Cite?
AbstractThe prediction of a time series using the dynamical systems approach requires the knowledge of three parameters; the time delay, the embedding dimension and the number of nearest neighbours. In this paper, a new criterion, based on the generalized degrees of freedom, for the selection of the number of nearest neighbours needed for a better local model for time series prediction is presented. The validity of the proposed method is examined using time series, which are known to be chaotic under certain initial conditions (Lorenz map, Henon map and Logistic map), and real hydro meteorological time series (discharge data from Chao Phraya river in Thailand, Mekong river in Thailand and Laos, and sea surface temperature anomaly data). The predicted results are compared with observations, and with similar predictions obtained by using arbitrarily fixed numbers of neighbours. The results indicate superior predictive capability as measured by the mean square errors and coefficients of variation by the proposed approach when compared with the traditional approach of using a fixed number of neighbours. © 2002 Elsevier Science B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/82743
ISSN
2015 Impact Factor: 3.043
2015 SCImago Journal Rankings: 1.743
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorJayawardena, AWen_HK
dc.contributor.authorLi, WKen_HK
dc.contributor.authorXu, Pen_HK
dc.date.accessioned2010-09-06T08:32:54Z-
dc.date.available2010-09-06T08:32:54Z-
dc.date.issued2002en_HK
dc.identifier.citationJournal Of Hydrology, 2002, v. 258 n. 1-4, p. 40-57en_HK
dc.identifier.issn0022-1694en_HK
dc.identifier.urihttp://hdl.handle.net/10722/82743-
dc.description.abstractThe prediction of a time series using the dynamical systems approach requires the knowledge of three parameters; the time delay, the embedding dimension and the number of nearest neighbours. In this paper, a new criterion, based on the generalized degrees of freedom, for the selection of the number of nearest neighbours needed for a better local model for time series prediction is presented. The validity of the proposed method is examined using time series, which are known to be chaotic under certain initial conditions (Lorenz map, Henon map and Logistic map), and real hydro meteorological time series (discharge data from Chao Phraya river in Thailand, Mekong river in Thailand and Laos, and sea surface temperature anomaly data). The predicted results are compared with observations, and with similar predictions obtained by using arbitrarily fixed numbers of neighbours. The results indicate superior predictive capability as measured by the mean square errors and coefficients of variation by the proposed approach when compared with the traditional approach of using a fixed number of neighbours. © 2002 Elsevier Science B.V. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jhydrolen_HK
dc.relation.ispartofJournal of Hydrologyen_HK
dc.rightsJournal of Hydrology. Copyright © Elsevier BV.en_HK
dc.subjectChaosen_HK
dc.subjectGeneralized degrees of freedomen_HK
dc.subjectHydrological time seriesen_HK
dc.subjectLocal modelsen_HK
dc.subjectNeighbourhood selectionen_HK
dc.titleNeighbourhood selection for local modelling and prediction of hydrological time seriesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0022-1694&volume=258&spage=40&epage=57&date=2002&atitle=Neighbourhood+selection+for+local+modelling+and+prediction+of+hydrological+time+seriesen_HK
dc.identifier.emailLi, WK: hrntlwk@hku.hken_HK
dc.identifier.authorityLi, WK=rp00741en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/S0022-1694(01)00557-1en_HK
dc.identifier.scopuseid_2-s2.0-0037186356en_HK
dc.identifier.hkuros65825en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0037186356&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume258en_HK
dc.identifier.issue1-4en_HK
dc.identifier.spage40en_HK
dc.identifier.epage57en_HK
dc.identifier.isiWOS:000173810800003-
dc.publisher.placeNetherlandsen_HK
dc.identifier.scopusauthoridJayawardena, AW=7005049253en_HK
dc.identifier.scopusauthoridLi, WK=14015971200en_HK
dc.identifier.scopusauthoridXu, P=8440784800en_HK

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