Publication:
Adaptive neuro-fuzzy inference technique for estimation of light penetration in reservoirs

dc.contributor.authorSoyupak, Selçuk
dc.contributor.authorŞentürk, Engin
dc.contributor.authorHekim, Hüseyin
dc.contributor.buuauthorKaraer, Feza
dc.contributor.departmentMühendislik Mimarlık Fakültesi
dc.contributor.departmentÇevre Mühendisliği Bölümü
dc.contributor.researcheridAAH-3984-2021
dc.contributor.scopusid6602782136
dc.date.accessioned2024-03-01T05:24:04Z
dc.date.available2024-03-01T05:24:04Z
dc.date.issued2007-02-05
dc.description.abstractAn adaptive neuro-fuzzy inference technique has been adopted to estimate light levels in a reservoir. The data were collected randomly from Doganci Dam Reservoir over a number of years. The input data set is a matrix with vectors of time, depth, sampling location, and incident solar radiation. The output data set is a vector representing light measured at various depths. Randomization and logarithmic transformations have been applied as preprocessing. One-half of the data have been utilized for training; testing and validation steps utilized one-fourth each. An adaptive neuro-fuzzy inference system (ANFIS) has been built as a prediction model for light penetration. Very high correlation values between predictions and real values on light measurements with relatively low root mean square error values have been obtained for training, test, and validation data sets. Elimination of the overtraining problem was ensured by satisfying close root mean square error values for all sets.
dc.identifier.citationKaraer, F. vd. (2007). "Adaptive neuro-fuzzy inference technique for estimation of light penetration in reservoirs". Limnology, 8(2), 103-112.
dc.identifier.endpage112
dc.identifier.issn1439-8621
dc.identifier.issue2
dc.identifier.scopus2-s2.0-34547943291
dc.identifier.startpage103
dc.identifier.urihttps://doi.org/10.1007/s10201-007-0204-6
dc.identifier.urihttps://link.springer.com/article/10.1007/s10201-007-0204-6
dc.identifier.urihttps://hdl.handle.net/11452/40103
dc.identifier.volume8
dc.identifier.wos000248820400003
dc.indexed.wosSCIE
dc.language.isoen
dc.publisherSpringer
dc.relation.collaborationYurt içi
dc.relation.collaborationSanayi
dc.relation.journalLimnology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectANFIS
dc.subjectReservoirs
dc.subjectLight penetration
dc.subjectNeuro-fuzzy inference
dc.subjectModeling
dc.subjectNew-York
dc.subjectLakes
dc.subjectTripton
dc.subjectMarine & freshwater biology
dc.subject.scopusSilicic Acid; Silicon Dioxide; Produced Water
dc.subject.wosLimnology
dc.titleAdaptive neuro-fuzzy inference technique for estimation of light penetration in reservoirs
dc.typeArticle
dc.wos.quartileQ3 (Limnology)
dspace.entity.typePublication
local.contributor.departmentMühendislik Mimarlık Fakültesi/Çevre Mühendisliği Bölümü
local.indexed.atPubMed
local.indexed.atScopus

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