Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1193
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dc.contributorDepartment of Civil and Environmental Engineering-
dc.creatorCheng, C-
dc.creatorZhao, MY-
dc.creatorChau, KW-
dc.creatorWu, X-
dc.date.accessioned2014-12-11T08:25:42Z-
dc.date.available2014-12-11T08:25:42Z-
dc.identifier.issn0022-1694-
dc.identifier.urihttp://hdl.handle.net/10397/1193-
dc.language.isoenen_US
dc.rightsJournal of Hydrology © 2005 Elsevier B.V. The journal web site is located at http://www.sciencedirect.com.en_US
dc.subjectGenetic algorithmen_US
dc.subjectRainfall-runoff modelen_US
dc.subjectCalibrationen_US
dc.subjectMultiple objectivesen_US
dc.subjectTOPSISen_US
dc.titleUsing genetic algorithm and TOPSIS for Xinanjiang model calibration with a single procedureen_US
dc.typeJournal/Magazine Articleen_US
dc.description.otherinformationAuthor name used in this publication: Chun-Tian Chengen_US
dc.description.otherinformationAuthor name used in this publication: K. W. Chauen_US
dc.description.otherinformationAuthor name used in this publication: Xin-yu Wuen_US
dc.identifier.spage129-
dc.identifier.epage140-
dc.identifier.volume316-
dc.identifier.issue1-4-
dc.identifier.doi10.1016/j.jhydrol.2005.04.022-
dcterms.abstractGenetic Algorithm (GA) is globally oriented in searching and thus useful in optimizing multiobjective problems, especially where the objective functions are ill-defined. Conceptual rainfall–runoff models that aim at predicting streamflow from the knowledge of precipitation over a catchment have become a basic tool for flood forecasting. The parameter calibration of a conceptual model usually involves the multiple criteria for judging the performances of observed data. However, it is often difficult to derive all objective functions for the parameter calibration problem of a conceptual model. Thus, a new method to the multiple criteria parameter calibration problem, which combines GA with TOPSIS (technique for order performance by similarity to ideal solution) for Xinanjiang model, is presented. This study is an immediate further development of authors' previous research (Cheng, C.T., Ou, C.P., Chau, K.W., 2002. Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall–runoff model calibration. Journal of Hydrology, 268, 72–86), whose obvious disadvantages are to split the whole procedure into two parts and to become difficult to integrally grasp the best behaviors of model during the calibration procedure. The current method integrates the two parts of Xinanjiang rainfall–runoff model calibration together, simplifying the procedures of model calibration and validation and easily demonstrated the intrinsic phenomenon of observed data in integrity. Comparison of results with two-step procedure shows that the current methodology gives similar results to the previous method, is also feasible and robust, but simpler and easier to apply in practice.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of hydrology, 10 Jan. 2006, v. 316, no. 1-4, p. 129-140-
dcterms.isPartOfJournal of hydrology-
dcterms.issued2006-01-
dc.identifier.isiWOS:000234275900010-
dc.identifier.scopus2-s2.0-28744454934-
dc.identifier.rosgroupidr29870-
dc.description.ros2005-2006 > Academic research: refereed > Publication in refereed journal-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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