2D CONVOLUTIONAL NEURAL NETWORK IN THE DESIGN OF MONOLITHIC SELFSTRESSED SLABS ON BASE
DOI:
https://doi.org/10.36773/1818-1112-2023-132-3-54-60Keywords:
convolutional neural network, neurons, slabs on base, self-stressed concrete, hybridAbstract
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 base has been developed a method that combines the advantages of theoretical models, and neural network technologies. The paper shows the possibility of using "soft computing", and also points out the promising potential of convolutional neural networks in predicting forced displacements in slabs of different geometrical shape.
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Copyright (c) 2023 Vestnik of Brest State Technical University
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