Classification of thermoluminescence features of CaCO3 with long short-term memory model

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dc.authorid0000-0002-6179-5746en_US
dc.contributor.authorIşık, Esme
dc.contributor.authorToktamış, Dilek
dc.contributor.authorEr, Mehmet Bilal
dc.contributor.authorHatib, Muhammed
dc.date.accessioned2021-08-17T21:04:53Z
dc.date.available2021-08-17T21:04:53Z
dc.date.issued2021en_US
dc.departmentMTÖ Üniversitesi, Darende Meslek Yüksekokulu, Tıbbi Hizmetler ve Teknikler Bölümüen_US
dc.description.abstractCalcium carbonate (CaCO3 ), a mineral commonly found in the Earth's crust, is mainly in the forms of calcite and aragonite. Calcite has the most stable type of thermodynamics at room temperature and ambient pressure. It has wide band gap structure and is of great interest for a wide-range technical and industrial applications due to its physical properties and suitability. In this study, a new method based on the long short-term memory (LSTM) model of deep learning is proposed to classify the thermoluminescence properties such as fading, cycle of measurement, heating rate, and dose-response of CaCO3 . Therefore the thermoluminescence properties of calcite was investigated as a suitable band structure and its coherent data were used to classify the features using a deep learning LSTM model. Experiments were carried out on a dataset consisting of four classes. The accuracy, precision, and sensitivity values of the proposed model obtained were 98.34, 97.90, and 98.56%, respectively. The classification process of the results obtained from the designed model showed good performance.en_US
dc.identifier.citationIsik, E., Toktamis, D., Er, M. B., & Hatib, M. Classification of Thermoluminescence Features of CaCO3 with Long Short‐Term Memory Model. Luminescence.en_US
dc.identifier.doi10.1002/bio.4109
dc.identifier.issn1522-7235en_US
dc.identifier.issn1522-7243en_US
dc.identifier.pmid34156748
dc.identifier.scopus2-s2.0-85110938798en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1002/bio.4109
dc.identifier.urihttps://hdl.handle.net/20.500.12899/330
dc.identifier.wosWOS:000675155100001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.institutionauthorIşık, Esme
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofLuminescenceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectLSTMen_US
dc.subjectCalciteen_US
dc.subjectDeep learningen_US
dc.subjectThermoluminescenceen_US
dc.titleClassification of thermoluminescence features of CaCO3 with long short-term memory modelen_US
dc.typeArticleen_US

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