A model for predicting drying time period of wool yarn bobbins using computational intelligence techniques

Basit Öğe Kaydı
dc.contributor.authorAkyol, Ugur
dc.contributor.authorTufekci, Pinar
dc.contributor.authorKahveci, Kamil
dc.contributor.authorCihan, Ahmet
dc.date.accessioned2024-03-13T10:32:58Z
dc.date.available2024-03-13T10:32:58Z
dc.date.issued2015
dc.departmentİstanbul Beykent Üniversitesien_US
dc.description.abstractIn this study, a predictive model has been developed using computational intelligence techniques for the prediction of drying time in the wool yarn bobbin drying process. The bobbin drying process is influenced by various drying parameters, 19 of which were used as input variables in the dataset. These parameters affect the drying time of yarn bobbins, which is considered as the target variable. The dataset, which consists of these input and target variables, was collected from an experimental yarn bobbin drying system. Firstly, the most effective input variables on the target variable, named as the best feature subset of the dataset, were investigated by using a filter-based feature selection method. As a result, the most important five parameters were obtained as the best feature subset. Afterwards, the most successful method that can predict the drying time of wool yarn bobbins with the highest accuracy was explored amongst the 16 computational intelligence methods for the best feature subset. Finally, the best performance has been found by the REP tree method, which achieved minimum error and time taken to build the model.en_US
dc.description.sponsorshipTUBITAK [108M274]en_US
dc.description.sponsorshipThis work was supported by TUBITAK (grant number 108M274).en_US
dc.identifier.doi10.1177/0040517514553879
dc.identifier.endpage1380en_US
dc.identifier.issn0040-5175
dc.identifier.issn1746-7748
dc.identifier.issue13en_US
dc.identifier.scopus2-s2.0-84930354858en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1367en_US
dc.identifier.urihttps://doi.org/10.1177/0040517514553879
dc.identifier.urihttps://hdl.handle.net/20.500.12662/3709
dc.identifier.volume85en_US
dc.identifier.wosWOS:000354440900005en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSage Publications Ltden_US
dc.relation.ispartofTextile Research Journalen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectprediction of drying timeen_US
dc.subjectwoolen_US
dc.subjectbobbinen_US
dc.subjectfeature selectionen_US
dc.subjectmachine learning regression methoden_US
dc.subjectREP tree methoden_US
dc.titleA model for predicting drying time period of wool yarn bobbins using computational intelligence techniquesen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu