New initialization approaches for the k-means and particle swarm optimization based clustering algorithms [K-ortalamalar ve parçacık sürü optimizasyonu tabanlı kümeleme algoritmaları için yeni ilklendirme yaklaşımları]

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dc.contributor.authorÇınaroğlu S.
dc.contributor.authorBulut H.
dc.date.accessioned2019-10-27T08:02:35Z
dc.date.available2019-10-27T08:02:35Z
dc.date.issued2018
dc.departmentEge Üniversitesien_US
dc.description.abstractIn this study a new risk assessment method for the evaluation of musculoskeletal disorders is proposed. “Musculoskeletal Discomfort Questionnaire” which was developed by Cornell University and widely used in the literature is adapted to fit the purpose of the study, and used as the data collection tool of the proposed method. The application of this method is conducted in a company that produces cable harnesses in the automotive supply industry and the musculoskeletal disorders of assembly line employees were identified (or diagnosed). The verification of the method was made using Rapid Entire Body Assessment (REBA), AnyBody Modelling System (AMS) analysis and Electromyography (EMG) measurements. The results show that the proposed method can be used successfully in prioritizing the work-related musculoskeletal system disorders (MSD), taking into account the intensity of the affected person. . © 2018 Gazi Universitesi Muhendislik-Mimarlik. All Rights Reserved.en_US
dc.identifier.doi10.17341/gazimmfd.416350
dc.identifier.endpage440en_US
dc.identifier.issn1300-1884
dc.identifier.issn1300-1884en_US
dc.identifier.issue2en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage425en_US
dc.identifier.urihttps://doi.org/10.17341/gazimmfd.416350
dc.identifier.urihttps://hdl.handle.net/11454/25211
dc.identifier.volume33en_US
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherGazi Universitesi Muhendislik-Mimarliken_US
dc.relation.ispartofJournal of the Faculty of Engineering and Architecture of Gazi Universityen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClusteringen_US
dc.subjectCoreseten_US
dc.subjectInitial centroid selectionen_US
dc.subjectK-meansen_US
dc.subjectParticle swarm optimizationen_US
dc.titleNew initialization approaches for the k-means and particle swarm optimization based clustering algorithms [K-ortalamalar ve parçacık sürü optimizasyonu tabanlı kümeleme algoritmaları için yeni ilklendirme yaklaşımları]en_US
dc.typeArticleen_US

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