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All issues Volume 531 (2024) E3S Web of Conf., 531 (2024) 03012 References
Open Access
Issue
E3S Web of Conf.
Volume 531, 2024
Ural Environmental Science Forum “Sustainable Development of Industrial Region” (UESF-2024)
Article Number 03012
Number of page(s) 9
Section Mathematical Modelling of Energy Systems
DOI https://doi.org/10.1051/e3sconf/202453103012
Published online 03 June 2024
  1. T. Nechay, V. Roganov, T. Zhachkova, M. Chircina, J. Lavendels, G. Korop, Improvement of operation planning for shunting service on non-public railway lines, in IOP Conference Series: Vol. 378 N 1. 14 November 2019. 012026. International Conference on innovations and Prospects of Development of Mining Machinery and Electrical Engineering 2019, IPDME 2019. Saint-Petersburg, 24 April 2019, 155535. ISSN 17551307, DOI 10.1088/1755-1315/378/1/012026 [Google Scholar]
  2. V. Roganov, L. Remontova, N. Esimova, S. Helal, Formation of a cognitive model of visual perception of 3D models in training complexes, in Lecture Notes in Information Systems and Organisation. Ser. “Digital Technologies in Teaching and Learning Strategies - Proceedings of DTTLS-2021” 2022. - pp. 58-66. [Google Scholar]
  3. M. Pyvovar, D. Kritskiy, T. Plastun, V. Kalashnikova, O. Popov, Takeoff and landing model of an aircraft in the aviation simulator, in Integrated Computer Technologies in Mechanical Engineering - 2021. Presents the proceedings of the ICTM? 21 Conference. Ser. “Lecture Notes in Networks and Systems” 2022. – pp. 364-372. [Google Scholar]
  4. N. Romancheva, O. Manolova, V. Michkasov, Procedural simulators as an element of the digital educational environment in the aviation specialist training, in CEUR Workshop Proceedings. “SLET 2020 - Proceedings of the International Scientific Conference on Innovative Approaches to the Application of Digital Technologies in Education” 2020. Russia (2020) [Google Scholar]
  5. M. Gołębiewski, M. Galant-Gołębiewska, R. Jasińsk, Flight simulator’s energy consumption depending on the conditions of the air operation, in Energies. 2022. Vol. 15. N 2. p. 580. DOI: 10.3390/en15020580 [CrossRef] [Google Scholar]
  6. V. R. Roganov, M.Yu. Mikheev, Resource management of a specialized flight area image synthesis system for an aviation simulator, in Aerospace instrumentation. 2023. N 3. pp. 48-60. DOI: 10.25791/aviakosmos.3.2023.1330 [Google Scholar]
  7. Vladimir Roganov, Boris Dolgovesov, Ekaterina Asmolova and Maria Chetvergova, Analysis of directions for improvement of flight simulators, in International Scientific Conference on Biotechnology and Food Technology (BFT-2023), Article Number 04037, Number of page(s) 7, Published online 11 December 2023, DOI: https://doi.org/10.1051/e3sconf/202346004037 [Google Scholar]
  8. Roganov V.R. Modeling the external environment for an aviation simulator. Monograph Publisher: IP Ar Media.2022 .-125 p. [Google Scholar]
  9. Vladimir Roganov, Boris Dolgovesov and Catherine Gudkova, E3S Web of Conf. Vol. 458, 2023. Article Number 03014, Number of page(s) 7, Published online 07 December 2023, DOI: https://doi.org/10.1051/e3sconf/202345803014 [Google Scholar]
  10. Dona, Loïs. Applying characteristics of human reasoning to zero-shot reasoning in GPT models. 2023. Thèse de maîtrise. [Google Scholar]
  11. Bang, Yejin, CAHYAWIJAYA, Samuel, LEE, Nayeon, et al. A multitask, multilingual, multimodal evaluation of chatgpt on reasoning, hallucination, and interactivity. arXiv preprint arXiv:2302.04023, 2023.. [Google Scholar]
  12. How GPT-3 changes the process of creating content in a cognitive visual environment / M. Yu. Mikheev, S. Helal, L. N. Pepel, E. A. Gudkova // Transactions of the International Symposium on Reliability and Quality. – 2023. – Vol. 2. – P. 279-280. [Google Scholar]
  13. The role of GPT-3 in natural language processing in a cognitive visual environment / M. Yu. Mikheev, S. Helal, L. N. Pepel, E. A. Gudkova // Transactions of the International Symposium on Reliability and Quality. – 2023. – Vol. 2. – P. 281-282. [Google Scholar]
  14. Cognitive visual environment for GPT-3 technology: conceptual aspects and technological foundations / M. Yu. Mikheev, S. Helal, L. N. Pepel, M. V. Chetvergova // Transactions of the International Symposium on Reliability and Quality. – 2023. – Vol. 2. – P. 277-278. [Google Scholar]
  15. Weston, Jason, BORDES, Antoine, CHOPRA, Sumit, et al. Towards ai-complete question answering: A set of prerequisite toy tasks. arXiv preprint arXiv:1502.05698, 2015. [Google Scholar]
  16. Dalvi, Bhavana, JANSEN, Peter, TAFJORD, Oyvind, et al. Explaining answers with entailment trees. arXiv preprint arXiv:2104.08661, 2021. [Google Scholar]
  17. Jessica López Espejel, El Hassane Ettifouri, Mahaman Sanoussi Yahaya Alassan, El Mehdi Chouham, Walid Dahhane, GPT-3.5, GPT-4, or BARD? Evaluating LLMs reasoning ability in zero-shot setting and performance boosting through prompts, Natural Language Processing Journal, Volume 5, 2023, 100032, https://doi.org/10.1016/j.nlp.2023.100032. [CrossRef] [Google Scholar]

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