Prediction of characteristic properties of crude oil blending with ANN

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dc.authorid0000-0002-3111-9042
dc.authorid0000-0002-2648-3931
dc.contributor.authorKaradurmuş, Erdal
dc.contributor.authorAkyazı, Habib
dc.contributor.authorGöz, Eda
dc.contributor.authorYüceer, Mehmet
dc.date.accessioned2019-05-10T09:39:40Z
dc.date.available2019-05-10T09:39:40Z
dc.date.issued2018
dc.departmentHitit Üniversitesi, Mühendislik Fakültesi, Kimya Mühendisliği Bölümü
dc.description.abstractMineral oil is one of the most important materials on earth and it is used widely for its several features. Mineral oils derived from petroleum products are commonly used to decrease the friction effects in machine parts and, thus, they both prevent wear/overheating and facilitate power transmission. In this study, various binary mixtures of various base oils (SN-80, SN-100, SN-150, SN-50, SN-500) were prepared at different volumetric ratios. Kinematic viscosity (at 40°C and 100°C), viscosity index, flash point, pour point, and density (at 20°C) measurements were performed for characterization of the prepared mixtures. These values were modeled by an artificial neural network (ANN) and the model was tested with root mean squared error (RMSE), mean absolute percentage error (MAPE, %), and regression coefficient (R) values. A higher value of correlation coefficient and smaller values of MAPE and RMSE indicate that the model performs better. For predicting kinematic viscosity at 40°C, correlation coefficients were calculated for training and testing the network as 0.9999 and 0.9995, respectively. Respective MAPE values were determined as 1.011% and 1.8771%. © 2017, © 2017 Taylor & Francis.
dc.identifier.citationKaradurmuş, E., Akyazı, H., Göz, E., & Yüceer, M. (2018). Prediction of characteristic properties of crude oil blending with ANN. Journal of Dispersion Science and Technology, 39(9), 1236-1243.
dc.identifier.doi10.1080/01932691.2017.1391702
dc.identifier.endpage1243en_US
dc.identifier.issn0193-2691
dc.identifier.issue9en_US
dc.identifier.scopusqualityQ2
dc.identifier.startpage1236en_US
dc.identifier.urihttps://doi.org/10.1080/01932691.2017.1391702
dc.identifier.urihttps://hdl.handle.net/11491/750
dc.identifier.volume39en_US
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherTaylor and Francis Inc.
dc.relation.ispartofJournal of Dispersion Science and Technology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectANNen_US
dc.subjectCrude Oil Blendingen_US
dc.titlePrediction of characteristic properties of crude oil blending with ANN
dc.typeArticle

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