Biochemical oxygen demand prediction in wastewater treatment plant by using different regression analysis models

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dc.authorid0000-0002-7553-9313en_US
dc.contributor.authorBaki, Osman Tugrul
dc.contributor.authorAras, Egemen
dc.contributor.authorAkdemir, Ummukulsum Ozel
dc.contributor.authorYilmaz, Banu
dc.date.accessioned2021-03-20T20:12:35Z
dc.date.available2021-03-20T20:12:35Z
dc.date.issued2019
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, İnşaat Mühendisliği Bölümüen_US
dc.description.abstractThe management and operation of the wastewater treatment plants (WWTP) have an important role in the controlling and monitoring of the plants' operations. Various performance data are taken into account in the controlling of the WWTP. The irregularities between operating parameters often lead to management problems that cannot be overcome. The aim of this study is to provide a simple and reliable prediction model to estimate the biochemical oxygen demand (BOD) with specific water quality parameters like wastewater temperature, pH, chemical oxygen demand, suspended sediment, total nitrogen, total phosphorus, electrical conductivity, and input discharge. The data records in this study were measured between June 2015 and May 2016 and obtained from the laboratory of Antalya Hurma WWTP. In the creation of the model, classical regression analysis, multivariate adaptive regression splines (MARS), artificial bee colony, and teaching-learning based optimization were used. The root mean square error and the mean absolute error were used to evaluate performance criteria for each model. When the results of the analyses were compared with each other, it was observed that the MARS method gave better estimation results than the other methods used in the study. As a result, it was evinced that the MARS method produces acceptable results in the BOD estimation.en_US
dc.identifier.doi10.5004/dwt.2019.24158en_US
dc.identifier.endpage89en_US
dc.identifier.issn1944-3994
dc.identifier.issn1944-3986
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage79en_US
dc.identifier.urihttp://doi.org/10.5004/dwt.2019.24158
dc.identifier.urihttps://hdl.handle.net/20.500.12885/622
dc.identifier.volume157en_US
dc.identifier.wosWOS:000470119100009en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.institutionauthorAras, Egemen
dc.language.isoenen_US
dc.publisherDesalination Publen_US
dc.relation.ispartofDesalination And Water Treatmenten_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBiochemical oxygen demanden_US
dc.subjectWastewater treatment planten_US
dc.subjectHeuristic regressionen_US
dc.subjectOptimization algorithmen_US
dc.titleBiochemical oxygen demand prediction in wastewater treatment plant by using different regression analysis modelsen_US
dc.typeArticleen_US

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