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M. F. Gafarov

Observed names: Gafarov, Maxim F., M.F. Gafarov, Maxim Gafarov
Observed institution: South Ural State University
ORCID: 0000-0001-8479-9363
Observed ORCID: 0000-0001-8479-9363
OpenAlex ID: A5046786263
Predicting the Hardness of Pipe Steels Using Machine Learning Methods
2022 · Maxim Gafarov, Konstantin Okishev, et al. · International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM) · 8
Construction of Models for Predicting the Microstructure of Steels after Heat Treatment Using Machine Learning Methods
2023 · M. F. Gafarov, K. Yu. Okishev, et al. · Steel in Translation · 5
Machine Learning Methods and Qualimetric Approach to Determine the Conditions for Train Students in the Field of Environmental and Economic Activities
2021 · Artem Salamatov, Elena Gafarova, et al. · International Journal of Emerging Technologies in Learning (iJET) · 4
Modeling of Material and Heat Balance of Ferromanganese Blast Furnace Smelting Using Computer Environment Lazarus
2019 · M.F. Gafarov, A.V. Senin, et al. · Materials science forum · 2
Development of a Material Selection Model for Rolls Rolling Mills Using Neural Networks
2020 · M.F. Gafarov, K.P. Pavlova, et al. · International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon) · 1
Modeling the proof strength of pipe steels tempered with the application of artificial intelligence methods
2024 · M. F. Gafarov, K. Yu. Okishev · Diagnostics Resource and Mechanics of materials and structures
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Modeling of decomposition products of supercooled austenite in pipe steels using artificial intelligence methods
2024 · M. F. Gafarov, K. Yu. Okishev, et al. · Ferrous Metallurgy Bulletin of Scientific Technical and Economic Information
Modeling of diagrams of hardenability of steels with using machine learning methods.
2023 · M. F. Gafarov, K. Yu. Okishev, et al. · Ferrous Metallurgy Bulletin of Scientific Technical and Economic Information
Modeling of Microstructure and Mechanical Properties of Pipe Steels After Heat Treatment Using Machine Learning Methods
2023 · Гафаров, М. Ф., Маковецкий, А. Н., et al. · Electronic Archive of Ural Federal University (ELAR UrFU)
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Works count: 9
Citation count: 20
H-index: 3
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