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http://hdl.handle.net/11452/23893
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yıldırım, Tacettin | - |
dc.contributor.author | Gasanly, Nizami Mamed | - |
dc.contributor.author | Özkan, Hüsnü | - |
dc.date.accessioned | 2022-01-06T08:56:15Z | - |
dc.date.available | 2022-01-06T08:56:15Z | - |
dc.date.issued | 2011-06 | - |
dc.identifier.citation | Küçük, İ. vd. (2011). "Estimation of thermally stimulated current in as grown TlGaSeS layered single crystals by multilayered perceptron neural network". Expert Systems with Applications, 38(6), 7192-7194. | en_US |
dc.identifier.issn | https://dl.acm.org/doi/abs/10.1016/j.eswa.2010.12.040 | - |
dc.identifier.issn | 0957-4174 | - |
dc.identifier.issn | 1873-6793 | - |
dc.identifier.uri | https://doi.org/10.1016/j.eswa.2010.12.040 | - |
dc.identifier.uri | http://hdl.handle.net/11452/23893 | - |
dc.description.abstract | This paper presents an artificial neural network approach to compute thermally stimulated current (TSC) in as-grown T1GaSeS layered single crystals. The experimental data have been obtained from TSC measurements. The network has been trained by a genetic algorithm (GA). The results confirmed that the proposed model could provide an accurate computation of the TSC. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Pergamon-Elsevier Science | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Computer science | en_US |
dc.subject | Engineering | en_US |
dc.subject | Operations research & management science | en_US |
dc.subject | Semiconductors | en_US |
dc.subject | Thermally stimulated current | en_US |
dc.subject | Neural network | en_US |
dc.subject | Genetic algorithm | en_US |
dc.subject | Optical-properties | en_US |
dc.subject | Trap distribution | en_US |
dc.subject | Absorption | en_US |
dc.subject | Photoconductivity | en_US |
dc.subject | Tlins2 | en_US |
dc.subject | Genetic algorithms | en_US |
dc.subject | Single crystals | en_US |
dc.subject | Thermoluminescence | en_US |
dc.subject | Artificial neural network approach | en_US |
dc.subject | As-grown | en_US |
dc.subject | Experimental data | en_US |
dc.subject | Multi-layered | en_US |
dc.subject | Perceptron neural networks | en_US |
dc.subject | Semiconductors | en_US |
dc.subject | Thermally stimulated current | en_US |
dc.subject | Neural networks | en_US |
dc.title | Estimation of thermally stimulated current in as grown TlGaSeS layered single crystals by multilayered perceptron neural network | en_US |
dc.type | Article | en_US |
dc.identifier.wos | 000288343900089 | tr_TR |
dc.identifier.scopus | 2-s2.0-79951579651 | tr_TR |
dc.relation.tubitak | 2218 | tr_TR |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi | tr_TR |
dc.contributor.department | Uludağ Üniversitesi/Fen-Edebiyat Fakültesi/Fizik Anabilim Dalı. | tr_TR |
dc.identifier.startpage | 7192 | tr_TR |
dc.identifier.endpage | 7194 | tr_TR |
dc.identifier.volume | 38 | tr_TR |
dc.identifier.issue | 6 | tr_TR |
dc.relation.journal | Expert Systems with Applications | en_US |
dc.contributor.buuauthor | Küçük, İlker Semih | - |
dc.subject.wos | Computer science, artificial intelligence | en_US |
dc.subject.wos | Engineering, electrical & electronic | en_US |
dc.subject.wos | Operations research & management science | en_US |
dc.indexed.wos | SCIE | en_US |
dc.indexed.scopus | Scopus | en_US |
dc.wos.quartile | Q1 | en_US |
dc.contributor.scopusid | 6602910810 | tr_TR |
dc.subject.scopus | Layered Semiconductors; Thermoluminescence; Mixed Crystals | en_US |
Appears in Collections: | Scopus Web of Science |
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