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dc.contributor.authorBayram, A.
dc.contributor.authorKankal, M.
dc.contributor.authorOzsahin, T.S.
dc.contributor.authorSaka, F.
dc.date.accessioned2021-11-09T19:37:37Z
dc.date.available2021-11-09T19:37:37Z
dc.date.issued2011
dc.identifier.issn10184619
dc.identifier.urihttps://hdl.handle.net/20.500.12440/2999
dc.description.abstractOrganic waste constitutes a majority of all municipal solid waste (MSW), a fact which yields some unfavorable results at open dumps, sanitary landfills, and incineration plants. As part of an integrated solid waste management strategy, composting could be applied to mixed collected MSWs or separately collected leaves, food, and yard wastes. The factor most crucial to successful composting is the carbon to nitrogen (C:N) ratio of the waste. This study employs two predictive models to estimate the C:N ratio of compostable MSW, an artificial neural network (ANN) and multiple linear regression (MLR). These models are based on 52 solid waste samples taken from the MSW open dumping area in Gümüşhane Province, Turkey. To estimate the C:N ratio, seven predictive variables were adopted. The proportions of food and yard (F&Y), and ash and scoria (A&S) waste; the moisture content (MC), the fixed carbon (FC) content, the total amount of organic matter (TOM), high calorific value (HCV), and pH. Fortytwo of the samples were used for training, and the remaining ten were used to test the models. The average relative error attained by the best ANN was 6.376%, while that attained by the MLR model was 11.002%. The effects of TOM content, F&Y percentage, and A&S percentage on the C:N ratio were investigated by running the ANN model for a range of input variables. © by PSP.en_US
dc.language.isoengen_US
dc.relation.ispartofFresenius Environmental Bulletinen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial neural network; C:N ratio; Composting; Municipal solid wasteen_US
dc.titleEstimation of the carbon to nitrogen (C:N) ratio in compostable solid waste using artificial neural networksen_US
dc.typearticleen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.description.scopuspublicationid2-s2.0-84856291928en_US
dc.department[Belirlenecek]en_US
dc.identifier.volume20en_US
dc.identifier.issue12 Aen_US
dc.identifier.startpage3250en_US
dc.contributor.institutionauthor[Belirlenecek]
dc.identifier.endpage3257en_US
dc.authorscopusid22133503300
dc.authorscopusid24471611900
dc.authorscopusid56156118800
dc.authorscopusid54926200700


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