Prediction of the air permeability of woven fabrics using neural networks

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dc.contributor.authorCay, Ahmet
dc.contributor.authorVassiliadis, Savvas
dc.contributor.authorRangoussi, Maria
dc.contributor.authorTarakcioglu, Isik
dc.date.accessioned2019-10-27T19:38:01Z
dc.date.available2019-10-27T19:38:01Z
dc.date.issued2007
dc.departmentEge Üniversitesien_US
dc.description.abstractPurpose - The target of the current work is the creation of a model for the prediction of the air permeability of the woven fabrics and the water content of the fabrics after the vacuum drying. Design/methodology/approach - There have been produced 30 different woven fabrics under certain weft and warp densities. The values of the air permeability and water content after the vacuum drying have been measured using standard laboratory techniques. The structural parameters of the fabrics and the measured values have been correlated using techniques like multiple linear regression and Artificial Neural Networks (ANN). The ANN and especially the generalized regression ANN permit the prediction of the air permeability of the fabrics and consequently of the water content after vacuum drying. The performance of the related models has been evaluated by comparing the predicted values with the respective experimental ones. Findings - The predicted values from the nonlinear models approach satisfactorily the experimental results. Although air permeability of the textile fabrics is a complex phenomenon, the nonlinear modeling becomes a useful tool for its prediction based on the structural data of the woven fabrics. Originality/value - The air permeability and water content modeling support the prediction of the related physical properties of the fabric based on the design parameters only. The vacuum drying performance estimation supports the optimization of the industrial drying procedure.en_US
dc.identifier.doi10.1108/09556220710717026
dc.identifier.endpage35en_US
dc.identifier.issn0955-6222
dc.identifier.issn1758-5953
dc.identifier.issn0955-6222en_US
dc.identifier.issn1758-5953en_US
dc.identifier.issue01.Feben_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage18en_US
dc.identifier.urihttps://doi.org/10.1108/09556220710717026
dc.identifier.urihttps://hdl.handle.net/11454/40038
dc.identifier.volume19en_US
dc.identifier.wosWOS:000244955000003en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherEmerald Group Publishing Ltden_US
dc.relation.ispartofInternational Journal of Clothing Science and Technologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectairen_US
dc.subjectpermeabilityen_US
dc.subjectneural netsen_US
dc.subjectporosityen_US
dc.subjectdryingen_US
dc.subjectmodellingen_US
dc.titlePrediction of the air permeability of woven fabrics using neural networksen_US
dc.typeArticleen_US

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