Comparision of the multiple regression, ann, and ANFIS models for prediction of MOE value of OSB panels

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dc.contributor.authorYapici, F.
dc.contributor.authorSenyer, N.
dc.contributor.authorEsen, R.
dc.date.accessioned2024-09-29T16:21:24Z
dc.date.available2024-09-29T16:21:24Z
dc.date.issued2016
dc.departmentKarabük Üniversitesien_US
dc.description.abstractThis research investigates the prediction of modulus of elasticity (MOE) properties, which is the most important properties in many applications, of the oriented strand board (OSB) produced under different conditions (pressing time, pressing pressure, pressing temperature and adhesive ratios) by multiple regression, artificial neural network (ANN) and adaptive Neurofuzzy inference system (ANFIS). Software computing techniques are now being used instead of statistical methods. It was found that the constructed ANFIS exhibited a higher performance than multiple regression and ANN for predicting MOE.Software computing techniques are very useful for precision industrial applications and, also determining which method gives the highest accurate result.en_US
dc.identifier.endpage754en_US
dc.identifier.issn1336-4561
dc.identifier.issue5en_US
dc.identifier.scopus2-s2.0-84991577002en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage741en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14619/9742
dc.identifier.volume61en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherStatny Drevarsky Vyskumny Ustaven_US
dc.relation.ispartofWood Researchen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectANFISen_US
dc.subjectANNen_US
dc.subjectMechanical propertiesen_US
dc.subjectMultiple regressionen_US
dc.subjectOSBen_US
dc.titleComparision of the multiple regression, ann, and ANFIS models for prediction of MOE value of OSB panelsen_US
dc.typeArticleen_US

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