employee
Voronezh, Voronezh, Russian Federation
Russian Federation
UDK 625 Дороги. Железные дороги. Железнодорожное строительство. Автомобильные дороги. Дорожное строительство
The article discusses the use of the popular BIM technology, its ease of use, economic feasibility and real assistance to engineers in their work. Examples of improvements in information modeling, the benefits of using a digital twin and artificial intelligence are considered. Machine learning methods contribute to the processing, systematization, forecasting and classification of large volumes of information based on certain criteria, which significantly reduces labor costs and increases work efficiency. The use of artificial intelligence algorithms simplifies the classification of BIM models of capital construction projects and prevents errors when entering data. During the study, a comparison was made between multidimensional analysis and an artificial neural network, the results of which confirmed the high efficiency of artificial intelligence training.
modeling, BIM technologies, highways, construction, advanced technologies, artificial intelligence, digital twin, neural network
1. Petrenko, D. A. BIM-resheniya «IndoSoft» dlya proektirovaniya i ekspluatacii avtomobil'nyh dorog / D. A. Petrenko, S. A. Subbotin // SAPR i GIS avtomobil'nyh dorog. – 2015. – № 2(5). – S. 100-107.
2. Abramyan, S.G. BIM-tehnologii v stroitel'stve: funkcii, razvitie i opyt primeneniya / S. G. Abramyan, O. V. Burlachenko, O. V. Oganesyan, A. O. Burlachenko, A. R. Shaunusov // Vestnik Volgogradskogo gosudarstvennogo arhitekturno-stroitel'nogo universiteta. Seriya: Stroitel'stvo i arhitektura. – 2021. – Vyp. 1(82). – S. 323-332.
3. Morozova, A. S. Autodesk o dorozhnom proektirovanii: problemy i resheniya / A. S. Morozova // SAPR i GIS avtomobil'nyh dorog. – 2014. – № 2(3). – S 63-66.
4. Petrenko, D. A., Subbotin S.A. BIM-resheniya «IndoSoft» dlya proektirovaniya i ekspluatacii avtomobil'nyh dorog // SAPR i GIS avtomobil'nyh dorog. 2015. № 2(5). – S. 100-107.
5. Babushkina, N.E. Reshenie zadachi opredeleniya mehanicheskih svoystv materialov dorozhnyh konstrukciy s ispol'zovaniem neyrosetevyh tehnologiy / N. E. Babushkina, A. A. Lyapin // Donskoy gosudarstvennyy tehnicheskiy universitet, g. Rostov-na-Donu / Advanced Engineerch 2022. T. 22. – № 3. – S. 285-291.
6. Badenko, V. L. Integration of digital twin and BIM technologies within factories of the future / V. L. Badenko., N. S Bolshakov, E. B. Tishchenko [et al.] // Magazine of Civil Engineering. – 2021. – No. 1(101). – P. 10114. – DOI:https://doi.org/10.34910/MCE.101.14.
7. Bobrova, T.V. Adekvatnost' proektnoy modeli avtomobil'noy dorogi real'nomu ob'ektu v kontekste cifrovoy transformacii / T.V. Bobrova, // Construction and Geotechnics. – 2023. – T. 14, – № 4. – S. 34–45. DOI:https://doi.org/10.15593/2224-9826/2023.4.03
8. Autodesk University 2023 polnost'yu posvyaschen iskusstvennomu intellektu: https://vk.com/@bim_tech-autodesk-university-2023-polnostu-posvyaschen-iskusstvennomu (data obrascheniya: 13.04.2024).
9. Dell’Acqua, G. Using Artificial Neural Network and Multivariate Analysis Techniques to Evaluate Road Operating Conditions / G. Dell’Acqua, M. De Luca, D. Zilioniene / Journal of Risk Research. – 2018. – Vol. 21. – R. 679–691. URL: https://doi.org/10.1080/13669877.2016.1264445 (data obrascheniya: 04.04.2024).
10. Otchet. Ocenka primeneniya BIM-tehnologiy v stroitel'stve. Rezul'taty issledovaniya effektivnosti primeneniya BIM-tehnologiy v investicionno-stroitel'nyh proektah rossiyskih kompaniy: https://www.nopriz.ru/upload/iblock/2cc/4.7_bim_rf_otchot.pdf Moskva, 2016. (data obrascheniya: 16.04.2024).
