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Using Neural Networks in Atomic Energy Thermophysical Problems (Review)

Zabirov, A. R., Smirnova, A. A., Feofilaktova, Y. M., Shevchenko, R. A., Shevchenko, S. A., Yashnikov, D. A., & Soloviev, S. L. (2020). Using Neural Networks in Atomic Energy Thermophysical Problems (Review). Thermal Engineering, 67(8), 497-508+. https://doi.org/10.1134/s0040601520080108 (Original work published 2025)

Leak localization using distributed sensors and machine learning for hydrogen releases from a fuel cell vehicle in a parking garage

Zhao, M. B., Huang, T. ., Liu, C. H., Chen, M. J., Ji, S. ., Christopher, D. M., & Li, X. F. (2021). Leak localization using distributed sensors and machine learning for hydrogen releases from a fuel cell vehicle in a parking garage. International Journal of Hydrogen Energy, 46(1), 1420-1433+. https://doi.org/10.1016/j.ijhydene.2020.09.218 (Original work published 2025)

Gas detonation cell width prediction model based on support vector regression

. Y. Yu, J. ., Hou, B. X., Lelyakin, A. ., Xu, Z. J., & Jordan, T. . (2017). Gas detonation cell width prediction model based on support vector regression. Nuclear Engineering and Technology, 49(7), 1423-1430+. https://doi.org/10.1016/j.net.2017.06.014 (Original work published 2025)
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