Modeling of Removal of Chromium (VI) from Aqueous Solutions Using Artificial Neural Network

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dc.contributor.authorTumer, Erdal Abdullah
dc.contributor.authorEdebali, Serpil
dc.contributor.authorGulcu, Saban
dc.date.accessioned2024-02-23T14:34:26Z
dc.date.available2024-02-23T14:34:26Z
dc.date.issued2020
dc.departmentNEÜen_US
dc.description.abstractThere is a need for knowledge, experience, laboratory, materials, and time to conduct chemical experiments. The results depend on the process and are also quite costly. For economic and rapid results, chemical processes can be modeled by utilizing data obtained in the past. In this paper, an artificial neural network model is proposed for predicting the removal efficiency of Cr (VI) from aqueous solutions with Amberlite IRA-96 resin, as being independent of chemical processes. Multiple linear regression, linear and quadratic particle swarm optimization are also used to compare prediction success. A total of 34 experimental data were used for training and validation of the model. pH, amount of resin, contact time, and concentration were used as input data. The removal efficiency is considered as output data for each model. The statistical methods of root-mean-square error, mean absolute percentage error, variance absolute relative error, and the coefficient of determination were used to evaluate the performance of the developed models. The system has been analyzed using a feature selection method to assess the influence of input parameters on the sorption efficiency. The most significant factor was found in pH. The obtained results show that the proposed ANN model is more reliable than the other models for estimating removal efficiency.en_US
dc.identifier.doi10.30492/IJCCE.2020.33257
dc.identifier.endpage175en_US
dc.identifier.issn1021-9986
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85089463038en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage163en_US
dc.identifier.urihttps://doi.org/10.30492/IJCCE.2020.33257
dc.identifier.urihttps://hdl.handle.net/20.500.12452/15618
dc.identifier.volume39en_US
dc.identifier.wosWOS:000600017900014en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherJihad Daneshgahien_US
dc.relation.ispartofIranian Journal Of Chemistry & Chemical Engineering-International English Editionen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial Neural Networken_US
dc.subjectMultilinear Regressionen_US
dc.subjectParticle Swarm Optimizationen_US
dc.subjectCr(Vi) Removalen_US
dc.subjectModelingen_US
dc.titleModeling of Removal of Chromium (VI) from Aqueous Solutions Using Artificial Neural Networken_US
dc.typeArticleen_US

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