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]

Çınaroğlu S.Bulut H.2019-10-272019-10-2720181300-18841300-1884https://doi.org/10.17341/gazimmfd.416350https://hdl.handle.net/11454/25211In 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.tr10.17341/gazimmfd.416350info:eu-repo/semantics/closedAccessClusteringCoresetInitial centroid selectionK-meansParticle swarm optimizationNew 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]Article332425440Q2