River flow estimation from upstream flow records by artificial intelligence methods

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dc.contributor.authorTuran M.E.
dc.contributor.authorYurdusev M.A.
dc.date.accessioned2024-07-22T08:21:44Z
dc.date.available2024-07-22T08:21:44Z
dc.date.issued2009
dc.description.abstractWater resources management has become more and more crucial by the depletion of available water resources to use as opposed to the increase of the water consumption. An effective management relies on accurate and complete information about the river on which a project will be constructed. Artificial intelligence techniques are often and successfully used to complete the unmeasured data. In this study, feed forward back propagation neural networks, generalized regression neural network, fuzzy logic are used to estimate unmeasured data using the data of the four runoff gauge station on the Birs River in Switzerland. The performances of these models are measured by the mean square error, determination coefficients and efficiency coefficients to choose the best fit model. © 2009 Elsevier B.V. All rights reserved.
dc.identifier.DOI-ID10.1016/j.jhydrol.2009.02.004
dc.identifier.issn00221694
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/18755
dc.language.isoEnglish
dc.subjectBirs River
dc.subjectCentral Europe
dc.subjectEurasia
dc.subjectEurope
dc.subjectSwitzerland
dc.subjectArtificial intelligence
dc.subjectBackpropagation
dc.subjectEstimation
dc.subjectFuzzy logic
dc.subjectFuzzy neural networks
dc.subjectFuzzy sets
dc.subjectHydrology
dc.subjectInformation management
dc.subjectRivers
dc.subjectStream flow
dc.subjectWater supply
dc.subjectArtificial intelligence methods
dc.subjectArtificial intelligence techniques
dc.subjectArtificial neural networks
dc.subjectBest-fit models
dc.subjectComplete informations
dc.subjectDetermination coefficients
dc.subjectEffective managements
dc.subjectEfficiency coefficients
dc.subjectFeed forward back propagation
dc.subjectGeneralized regression neural networks
dc.subjectMean squares
dc.subjectRiver flow estimation
dc.subjectSwitzerland
dc.subjectUpstream flows
dc.subjectWater consumption
dc.subjectWater resources managements
dc.subjectartificial neural network
dc.subjectback propagation
dc.subjectfuzzy mathematics
dc.subjecthydrology
dc.subjectnumerical model
dc.subjectregression analysis
dc.subjectriver flow
dc.subjectstreamflow
dc.subjectwater resource
dc.subjectwater use
dc.subjectWater resources
dc.titleRiver flow estimation from upstream flow records by artificial intelligence methods
dc.typeArticle

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