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Data mining and pixel distribution approach for wood density prediction

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dc.contributor.author Bardak, Timuçin
dc.contributor.author Bardak, Selahattin
dc.contributor.author Sözen, Eser
dc.date.accessioned 2019-11-12T07:14:17Z
dc.date.available 2019-11-12T07:14:17Z
dc.date.issued 2019-08-15
dc.identifier.citation BARDAK, T., BARDAK, S., & SÖZEN, E. (2019). Data Mining and Pixel Distribution Approach for Wood Density Prediction. Journal of Bartin Faculty of Forestry, 19(2), 386-396. en_US
dc.identifier.uri http://hdl.handle.net/11772/1991
dc.description.abstract The wood material has strategic importance in economic development. Innovations are the basic premise of commercial success in the wood industry, as in all industries. The density of wood provides valuable information about the physical and mechanical properties of the wood, and it is also directly related to the productivity in the forest industry. Many non-destructive test studies have been conducted to evaluate the physical properties of wood structures. This study was conducted to predict the density of wood in the species of oak (Quercus robur) and beech (Fagus orientalis L.) using the number of pixels in a grayscale image and data mining. To this purpose, pixel density of data was processed with the data collected from the images of wood specimens. This data was used as descriptor variables in artificial neural networks and random forest algorithm. The designed artificial neural network model and random forest algorithm allowed the prediction of density with an accuracy of 95.19% and 96.36%, respectively for the testing phase. As a result, this study showed that pixel density and data mining have the potential to be used as an instrument for predicting the density of wood. en_US
dc.language.iso tur en_US
dc.publisher Journal of Bartin Faculty of Forestry en_US
dc.relation.isversionof 10.24011/barofd.561858 en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Data mining en_US
dc.subject Artificial neural networks en_US
dc.subject Random forest en_US
dc.subject Digital images en_US
dc.subject Wood en_US
dc.subject Veri madenciliği en_US
dc.subject Yapay sinir ağları en_US
dc.subject Rastgele orman en_US
dc.subject Dijital görüntüler en_US
dc.subject Ahşap en_US
dc.title Data mining and pixel distribution approach for wood density prediction en_US
dc.title.alternative Odun yoğunluğu tahmini için veri madenciliği ve piksel dağılımı yaklaşımı en_US
dc.type article en_US
dc.relation.journal Journal of Bartin Faculty of Forestry en_US
dc.contributor.department Bartın Üniversitesi, Bartın Meslek Yüksekokulu, Mobilya ve Dekorasyon Bölümü en_US
dc.contributor.authorID 41015 en_US
dc.identifier.volume 19 en_US
dc.identifier.issue 2 en_US
dc.identifier.startpage 386 en_US
dc.identifier.endpage 396 en_US


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