BROMATE REMOVAL PREDICTION IN DRINKING WATER BY USING THE LEAST SQUARES SUPPORT VECTOR MACHINE (LS-SVM)

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dc.authoridYuceer, Mehmet/0000-0002-2648-3931
dc.authorwosidYuceer, Mehmet/E-5110-2012
dc.contributor.authorKaradurnius, Erdal
dc.contributor.authorGoz, Eda
dc.contributor.authorTaskin, Nur
dc.contributor.authorYuceer, Mehmet
dc.date.accessioned2024-08-04T20:53:31Z
dc.date.available2024-08-04T20:53:31Z
dc.date.issued2020
dc.departmentİnönü Üniversitesien_US
dc.description.abstractThe main objective of this study was to develop Least Squares Support Vector Machine (LS-SVM) algorithm for prediction of bromate removal in drinking water. Adsorption method known as environmental-friendly and economical was used in the experimental part of this study to remove this harmful compound from drinking water. Technically (pure), HCl-, NaOH- and NH3-modified activated carbons were prepared as adsorbent. Experimental studies were carried out with synthetic samples in three different concentrations. To forecast bromate removal percentage particle size and amount of the activated carbon, height and diameter of the column, volumetric flowrate, and initial concentration were selected as the input variables Radial basis kernel function was selected as activation function in algorithm. Algorithm parameters that gamma and sigma(2) values set as 415 and 3.956 respectively. To evaluate model performance some performance indices were calculated. Correlation coefficient (R), mean absolute percentage error (MAPE%) and root mean square error (RMSE) value for the training and testing phase R:0.996, MAPE%: 2.59 RMSE: 2.14 and R:0.994, MAPE%: 3.21 RMSE: 2.51 respectively. These results obtained from this study were compared with the ANN model previously developed with the same input data. As a result, LS-SVM has better performance than ANN.en_US
dc.description.sponsorshipHitit University Scientific Research Foundation [MUH19004.13.003]en_US
dc.description.sponsorshipThis study was supported by Hitit University Scientific Research Foundation (Project No: MUH19004.13.003).en_US
dc.identifier.endpage2153en_US
dc.identifier.issn1304-7205
dc.identifier.issn1304-7191
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85149986562en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage2145en_US
dc.identifier.urihttps://hdl.handle.net/11616/101224
dc.identifier.volume38en_US
dc.identifier.wosWOS:000603605300037en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherYildiz Technical Univen_US
dc.relation.ispartofSigma Journal of Engineering and Natural Sciences-Sigma Muhendislik Ve Fen Bilimleri Dergisien_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDrinking water treatmenten_US
dc.subjectbromate removalen_US
dc.subjectartificial intelligenceen_US
dc.subjectLS-SVMen_US
dc.titleBROMATE REMOVAL PREDICTION IN DRINKING WATER BY USING THE LEAST SQUARES SUPPORT VECTOR MACHINE (LS-SVM)en_US
dc.typeArticleen_US

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