Performance Analysis of Structural Agent Model Based on Artificial Neural Network
In the actual structure construction process,due to the characteristics of high-order static stability and strong nonlinearity,the calculation model applied to the immediate decision-making of the construction process is very complicated.Aiming at the problem that the explicit relationship of the specific structural response cannot be obtained during the construction process and the slow calculation of the finite element model applied to the instant decision,the use of the surrogate model to replace the structural response can greatly improve the computational efficiency.In this paper,the theory of the most widely used artificial neural network discussed.The fitting performance of BP neural network(BPNN)and general regression neural network(GRNN)is studied by a frame example.The comparison aims to provide a reference for the selection of structural surrogate models.
NETL
NSTL
万方数据
