Prediction of noise emission in the machining of wood materials by means of an artificial neural network

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dc.authorid0000-0001-8216-0048en_US
dc.authorid0000-0003-0884-2555en_US
dc.contributor.authorÖzşahin, Şükrü
dc.contributor.authorSinger, Hilal
dc.date.accessioned2023-09-28T08:12:46Z
dc.date.available2023-09-28T08:12:46Z
dc.date.issued2022en_US
dc.departmentBAİBÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.description.abstractBackground: Noise produced during machining of wood materials can be a source of harm to workers and an environmental hazard. Understanding the factors that contribute to this noise will aid the development of mitigation strategies. In this study, an artificial neural network (ANN) model was developed to model the effects of wood species, cutting width, number of blades, and cutting depth on noise emission in the machining process. Methods: A custom application created with MATLAB codes was used for the development of the multilayer feed-forward ANN model. Model performance was evaluated by numerical indicators such as MAPE, RMSE, and R-2. Results: The ANN model performed well with acceptable deviations. The MANE, RMSE, and R-2 values were 0.553%, 0.600, and 0.9824, respectively, in the testing phase. Furthermore, this study predicted the intermediate values not provided from the experimental study. The model predicted that lower noise emissions would occur with decreased cutting width and cutting depth. Conclusions: ANNs are quite effective in predicting the noise emission. Practitioners relying on the ANN approach for investigating the effects of various factors on noise emission can save time and costs by reducing the number of experimental combinations studied to generate predictive models.en_US
dc.identifier.citationÖzşahin, Ş., & Singer, H. (2022). Prediction of noise emission in the machining of wood materials by means of an artificial neural network. New Zealand Journal of Forestry Science, 52.en_US
dc.identifier.doi10.33494/nzjfs522022x92x
dc.identifier.endpage10en_US
dc.identifier.issn0048-0134
dc.identifier.issn1179-5395
dc.identifier.scopus2-s2.0-85129222833en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1en_US
dc.identifier.urihttp://dx.doi.org/10.33494/nzjfs522022x92x
dc.identifier.urihttps://hdl.handle.net/20.500.12491/11754
dc.identifier.volume52en_US
dc.identifier.wosWOS:000788086500001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorSinger, Hilal
dc.language.isoenen_US
dc.publisherScionen_US
dc.relation.ispartofNew Zealand Journal of Forestry Scienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectArtificial Neural Networken_US
dc.subjectNoise Emissionen_US
dc.subjectMachiningen_US
dc.subjectWooden_US
dc.subjectPredictionen_US
dc.subjectSaw Bladeen_US
dc.titlePrediction of noise emission in the machining of wood materials by means of an artificial neural networken_US
dc.typeArticleen_US

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