Prediction of reduced glass transition temperature of metallic alloys based on a neural network

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dc.contributor.authorViatkin, Dimitri
dc.contributor.authorZakharov, Maxim
dc.contributor.authorZhuro Vladimirovich, Dmitry
dc.date.accessioned2026-02-06T13:29:21Z
dc.date.available2026-02-06T13:29:21Z
dc.date.issued2022-12-16
dc.date.updated2026-02-06T13:29:21Z
dc.descriptionPonencia presentada en la III International Scientific Conference on Metrological Support of Innovative Technologies (ICMSIT III 2022), celebrada online entre el 3 y el 5 de marzo de 2022.es
dc.description.abstractThe reduced glass transition temperature Trg is an important glass forming ability parameter. Trg describes the glass formation in materials and the behaviour of materials at the transition between solid and liquid states and is an important parameter for materials analysis, development, and production process. This article describes the process and results of research on the development of a system for prediction of the reduced glass transition temperature Trg of metallic alloys based on recurrent neural network algorithms. The developed system can predict the reduced glass transition temperature Trg of metallic alloys based on the analysis of its chemical formula with high accuracy. The accuracy was evaluated using the 3 metrics: MSE, RMSE, MAE. Obtained values are: MSE value is 0.000678, RMSE value is 0.0260, MAE value is 0.01835.en
dc.identifier.citationViatkin, D., Zakharov, M., & Zhuro, D. (2022). Prediction of reduced glass transition temperature of metallic alloys based on a neural network. Journal of Physics: Conference Series, 2373(8). https://doi.org/10.1088/1742-6596/2373/8/082016
dc.identifier.doi10.1088/1742-6596/2373/8/082016
dc.identifier.eissn1742-6596
dc.identifier.issn1742-6588
dc.identifier.urihttps://hdl.handle.net/20.500.14454/5023
dc.language.isoeng
dc.publisherInstitute of Physics
dc.titlePrediction of reduced glass transition temperature of metallic alloys based on a neural networken
dc.typeconference paper
dcterms.accessRightsopen access
oaire.citation.issue8
oaire.citation.titleJournal of Physics: Conference Series
oaire.citation.volume2373
oaire.licenseConditionhttps://creativecommons.org/licenses/by/4.0/
oaire.versionVoR
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