A training-efficient Wiener-type neural network modeling approach for structural dynamic response prediction
A Wiener-type neural network based on CSNN is proposed by reducing the nonlinear state derivative calculator present in CSNN to a linear equation, and an explicit state expression for WNN that discards high-order differentiable items for back propagation is derived, which greatly enhances training efficiency.