Classification of Different Recycled Rubber-Epoxy Composite Based on Their Hardness Using Laser-Induced Breakdown Spectroscopy (libs) With Comparison Machine Learning Algorithms

dc.authorid aslan, ozgur/0000-0002-1042-0805
dc.authorscopusid 57201855036
dc.authorscopusid 22950638800
dc.authorscopusid 25521345500
dc.authorscopusid 12142980800
dc.contributor.author Yilmaz, Vadi Su
dc.contributor.author Yılmaz, Vadi Su
dc.contributor.author Eseller, Kemal Efe
dc.contributor.author Aslan, Ozgur
dc.contributor.author Aslan, Özgür
dc.contributor.author Bayraktar, Emin
dc.contributor.author Eseller, Kemal Efe
dc.contributor.author Yılmaz, Vadi Su
dc.contributor.author Aslan, Özgür
dc.contributor.author Eseller, Kemal Efe
dc.contributor.other Electrical-Electronics Engineering
dc.contributor.other Mechanical Engineering
dc.contributor.other Department of Electrical & Electronics Engineering
dc.contributor.other Department of Electrical & Electronics Engineering
dc.contributor.other Mechanical Engineering
dc.contributor.other Electrical-Electronics Engineering
dc.contributor.other Mechanical Engineering
dc.contributor.other Department of Electrical & Electronics Engineering
dc.date.accessioned 2024-07-05T15:25:09Z
dc.date.available 2024-07-05T15:25:09Z
dc.date.issued 2023
dc.department Atılım University en_US
dc.department-temp [Yilmaz, Vadi Su; Eseller, Kemal Efe] Atilim Univ, Dept Elect Elect Engn, TR-06830 Ankara, Turkiye; [Eseller, Kemal Efe] Univ Massachusetts Lowell, Dept Phys & Appl Phys, Lowell, MA 01854 USA; [Aslan, Ozgur] Atilim Univ, Dept Mech Engn, TR-06830 Ankara, Turkiye; [Bayraktar, Emin] ISAE Supmeca Paris, Sch Mech & Mfg Engn, F-93407 Paris, France en_US
dc.description aslan, ozgur/0000-0002-1042-0805 en_US
dc.description.abstract This paper aims toward the successful detection of harmful materials in a substance by integrating machine learning (ML) into laser-induced breakdown spectroscopy (LIBS). LIBS is used to distinguish five different synthetic polymers where eight different heavy material contents are also detected by LIBS. Each material intensity-wavelength graph is obtained and the dataset is constructed for classification by a machine learning (ML) algorithm. Seven popular machine learning algorithms are applied to the dataset which include eight different substances with their wavelength-intensity value. Machine learning algorithms are used to train the dataset, results are discussed and which classification algorithm is appropriate for this dataset is determined. en_US
dc.identifier.citationcount 0
dc.identifier.doi 10.3390/inventions8020054
dc.identifier.issn 2411-5134
dc.identifier.issue 2 en_US
dc.identifier.scopus 2-s2.0-85153715175
dc.identifier.uri https://doi.org/10.3390/inventions8020054
dc.identifier.uri https://hdl.handle.net/20.500.14411/2513
dc.identifier.volume 8 en_US
dc.identifier.wos WOS:000978185800001
dc.institutionauthor Yılmaz, Vadi Su
dc.institutionauthor Aslan, Özgür
dc.institutionauthor Eseller, Kemal Efe
dc.language.iso en en_US
dc.publisher Mdpi en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.scopus.citedbyCount 1
dc.subject LIBS en_US
dc.subject rubber-polymers en_US
dc.subject hardness en_US
dc.subject machine learning en_US
dc.subject classification en_US
dc.title Classification of Different Recycled Rubber-Epoxy Composite Based on Their Hardness Using Laser-Induced Breakdown Spectroscopy (libs) With Comparison Machine Learning Algorithms en_US
dc.type Article en_US
dc.wos.citedbyCount 1
dspace.entity.type Publication
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