Recursive long short-term memory network for predicting nonlinear structural seismic response

Artificial neural networks have been used to predict nonlinear structural time histories under seismic excitation because they have a significantly lower computational cost than the traditional time-step integration method. However, most existing techniques require simplification procedures such as downsampling to maintain identical length and sampling rates, and they lack sufficient accuracy, generality, or interpretability. In this paper, a...