Comparison of intelligent methods for predicting aeration efficiency of high-head conduits

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dc.authoridHanbay, Davut/0000-0003-2271-7865
dc.authorwosidHanbay, Davut/AAG-8511-2019
dc.contributor.authorUnsal, Mehmet
dc.contributor.authorHanbay, Davut
dc.date.accessioned2024-08-04T20:37:26Z
dc.date.available2024-08-04T20:37:26Z
dc.date.issued2012
dc.departmentİnönü Üniversitesien_US
dc.description.abstractThe ecological quality of water depends largely on amount of oxygen that the water can hold. Oxygen enters water by entrainment of air bubbles. There is a significant oxygen transfer associated with most hydraulic structures because the air entrained into the flow is split into small bubbles, which greatly increase the surface area for transfer. To design efficient hydraulic structures they must be modeled and analyzed correctly before they are realized. Different methods based on mathematical, statistical and intelligent methods are used for modeling and analyzing. In this paper, comparison of intelligent methods for predicting aeration efficiency of high-head conduits was presented. The intelligent methods used were Neural Network (NN), Adaptive Network based Fuzzy Inference Systems (ANFIS) and Least Squares Support Vector Machines (LS-SVM). The 3-k cross validation test was applied to evaluate the performance of intelligent methods. The predicted values were compared with the experimental measured values and R-2 statistics were calculated and tabulated. All methods have good agreement with experimental results. According to calculated statistics, the best performance was obtained with the LS-SVM model at R-2 0.9815.en_US
dc.identifier.endpage130en_US
dc.identifier.issn1024-8684
dc.identifier.issue2Ben_US
dc.identifier.scopus2-s2.0-84874340318en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage113en_US
dc.identifier.urihttps://hdl.handle.net/11616/95968
dc.identifier.volume39en_US
dc.identifier.wosWOS:000325240800006en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherAcademic Publication Councilen_US
dc.relation.ispartofKuwait Journal of Science & Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectHigh-head conduiten_US
dc.subjectaeration efficiencyen_US
dc.subjectair entrainmenten_US
dc.subjectNNen_US
dc.subjectANFISen_US
dc.subjectLS-SVMen_US
dc.titleComparison of intelligent methods for predicting aeration efficiency of high-head conduitsen_US
dc.typeArticleen_US

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