Comparison of artificial neural network and linear regression models for prediction of ring spun yarn properties. II. Prediction of yarn hairiness and unevenness

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dc.contributor.authorUreyen, Mustafa E.
dc.contributor.authorGurkan, Pelin
dc.date.accessioned2019-10-27T19:55:33Z
dc.date.available2019-10-27T19:55:33Z
dc.date.issued2008
dc.departmentEge Üniversitesien_US
dc.description.abstractThe objective of this second part of the study is to develop artificial neural network models for the prediction of yarn hairiness and unevenness and to compare the performance of ANN models with our previous statistical models based on regression analysis. Besides HVI properties, yarn count, twist and roving properties were also selected as input variables. Part 1 provided detailed description of experimental procedure of the study. Yarn hairiness and unevenness tests were performed on Uster Tester 3. Following the developed ANN models, sensitivity analysis results and coefficient of multiple determination (R-2) values of ANN and regression models were compared. Analyses are showed that ANN models improve the prediction performance with regards to regression models.en_US
dc.identifier.doi10.1007/s12221-008-0015-3
dc.identifier.endpage96en_US
dc.identifier.issn1229-9197
dc.identifier.issn1229-9197en_US
dc.identifier.issue1en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage92en_US
dc.identifier.urihttps://doi.org/10.1007/s12221-008-0015-3
dc.identifier.urihttps://hdl.handle.net/11454/40701
dc.identifier.volume9en_US
dc.identifier.wosWOS:000253546200015en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherKorean Fiber Socen_US
dc.relation.ispartofFibers and Polymersen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectartificial neural networken_US
dc.subjectlinear regressionen_US
dc.subjectring spun yarnen_US
dc.subjectyarn hairinessen_US
dc.subjectyarn unevennessen_US
dc.titleComparison of artificial neural network and linear regression models for prediction of ring spun yarn properties. II. Prediction of yarn hairiness and unevennessen_US
dc.typeArticleen_US

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