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В данной работе исследована возможность применения методов машинного обучения для оптимизации стержневой конструкции. Даны основные понятия нейронных сетей и изучены конкретные методы их обучения. Последовательно разработаны нейронные сети, предсказывающие потерю устойчивости стержней и дальнейшее их поведение с постепенным добавлением геометрических характеристик и граничных условий.
In this work, the possibility of using machine learning methods to optimize the bar structure was investigated. Basic concepts of neural networks are given, and specific methods of their training are studied. Neural networks have been consistently developed that predict the loss of stability of rods and their further behavior with the gradual addition of geometric characteristics and boundary conditions.
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