INVESTIGATION INTO AI-ASSISTED OPTIMIZATION OF THIN-WALLED CROSS-SECTIONS
DOI:
https://doi.org/10.30888/2709-2267.2025-31-00-018Ключові слова:
Artificial intelligence, Machine learning, Permanent formwork, Cross-section optimization, Surrogate modeling, Generative Design, Physics-informed neural networks, multi-fidelity data integration, Structural health monitoring, Hybrid AI-FEA workflows.Анотація
This research reviews the integration of artificial intelligence in structural cross-section selection, highlighting supervised learning, reinforcement learning, evolutionary algorithms, and physics-informed models as complementary methodologies. SupervisMetrics
Metrics Loading ...
Downloads
Опубліковано
2025-05-30
Як цитувати
Мовчан, О. (2025). INVESTIGATION INTO AI-ASSISTED OPTIMIZATION OF THIN-WALLED CROSS-SECTIONS. Sworld-Us Conference Proceedings, 1(usc31-00), 55–62. https://doi.org/10.30888/2709-2267.2025-31-00-018
Номер
Розділ
Тези
Ліцензія
Авторське право (c) 2025 Автори
Ця робота ліцензується відповідно до Creative Commons Attribution 4.0 International License.
