Neural Network Based Modelling of Soil Particle Diameters Under Varying Quantity of Sodium Hexametaphosphate

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dc.contributor.authorÖzgan, Ercan
dc.date.accessioned2020-04-30T23:19:30Z
dc.date.available2020-04-30T23:19:30Z
dc.date.issued2009
dc.departmentDÜ, Teknik Eğitim Fakültesi, Yapı Eğitimi Bölümüen_US
dc.descriptionWOS: 000264759100015en_US
dc.description.abstractIn this Study, the particle diameter of the soil was simulated and modelled by using artificial neural network method. In order to determine the particle diameter of the soil based on passing time, hydrometer reading, temperature of the solution and the quantity of the sodium hexametaphosphate, the quantity of the sodium hexametaphosphate 0, 10, 20, 30, 40, 50 and 60 were respectively selected. As pointed out in the Turkish Standard 1900, the soil particle diameters in the solution prepared with 40 g sodium hexametaphosphate was taken as reference. It was found that the average soil grain diameter for 0 g sodium hexametaphosphate was about 4.5 times bigger than the reference grain diameter, for 10 g was 3.9 times, for 20 g 3.46 times, for 30 g 2.12 times bigger. However, the hydrometer reading could be done only up to the 260th min for 50 g sodium hexametaphosphate and for 60 g sodium hexametaphosphate the hydrometer couldn't be read. The relationships between experimental results and artiflicial neural network (ANN) model exhibited good correlation. The cot-relation coefficients square were found as R(2) = 0.99 for training set and R(2) = 0.94 for testing set with ANN. Based on the result, of the study, it could be said that the ANN method could be used for modelling of the particle diameter of the soil according to the passing time, hydrometer reading, temperature of the and the quantity of the sodium hexametaphosphate.en_US
dc.identifier.endpage2642en_US
dc.identifier.issn0970-7077
dc.identifier.issue4en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage2632en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12684/3772
dc.identifier.volume21en_US
dc.identifier.wosWOS:000264759100015en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherAsian Journal Of Chemistryen_US
dc.relation.ispartofAsian Journal Of Chemistryen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial neural networken_US
dc.subjectHydrometer testen_US
dc.subjectParticle diameteren_US
dc.subjectSodium hexametaphosphateen_US
dc.titleNeural Network Based Modelling of Soil Particle Diameters Under Varying Quantity of Sodium Hexametaphosphateen_US
dc.typeArticleen_US

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