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    • 2d convolutional neural network in the design of monolithic self-stressed slabs on base 

      Zheltkovich, Andrey Evgenievich; Parchotz, Konstantin Gennadievich; Molosh, Victor Viktorovich; Jin Haotian; Xu Shang (БрГТУ, 2023)
      The purpose of this paper is to demonstrate the capabilities of convolutional neural networks in mechanics-related problems, in particular, in the design of monolithic self-stressed slabs on the base. In order to simplify the procedure of designing and calculating the displacements of slabs on the ...

      2024-02-14

    • Full connected neural-network for simulation of extantion in self-stressed monolitic slabs on ground 

      Zheltkovich, Andrey Evgenievich; Molosh, Viktor Viktorovich; Parchotz, Konstantin Gennadievich; Saveiko, Nikolai Gennadievich; Yuan Jinbin; Zhenhao Jiang; Zheng Haoyuan (BrSTU, 2022)
      In this article the strategy of interdisciplinary convergence of mechanics and artificial intelligence is illustrated. The article presents the results of calculating displacements in self-stressed monolithic slabs on ground obtained using a trained fully connected neural network. The empirical results ...

      2023-03-22